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status-publish has-post-thumbnail hentry entry"> <div class="entry-content"> <div id="slv168_t11_sm48_spgli" class="abcfslSPgCntr abcfslMLRAuto"><div><p class="STFFCAT-F2">Professor</p><h3 class="MP-F1"><span class="abcfslSpanMP2">Frank </span><span class="abcfslSpanMP3">Hutter </span></h3></div><div class="abcfslSPgCntrM abcfClrFix abcfslMT10"><div class="abcfslLstCol abcfslLstCol-3 abcfslImgColSPg"><div class="abcfslImgCntrSPg"><img decoding="async" src="https://ml.informatik.uni-freiburg.de/wp-content/uploads/people/frank_high_res.jpg" class="abcfslDShadow1 staff-list-profile-pic" alt="" itemprop="image" /></div></div><div class="abcfslLstCol abcfslLstCol-9 abcfslTxtColSPg"><div class="abcfslPadLPc5 abcfslCenter575"><div class="SC-F9" style="float:right;"> <a data-service="twitter" data-category="marketing" data-placeholder-image="http://ml.informatik.uni-freiburg.de/wp-content/plugins/complianz-gdpr/assets/images/placeholders/twitter-minimal.jpg" class="cmplz-placeholder-element twitter-timeline" data-width="" data-height="600" data-theme="light" href="https://twitter.com/FrankRHutter">Tweets by FrankRHutter</a> </div><div class="PT-F3" style="float:left;"><h6>Postal address</h6> Institut für Informatik<br> Albert-Ludwigs-Universität Freiburg<br> Sekretariat Hutter/Maschinelles Lernen<br> Georges-Köhler-Allee 074<br> 79110 Freiburg, Germany <h6>Fax</h6> +49 761 203-74217 <h6>Office</h6>Building 74, Room 00-017</div><div class="FONE-F5" style="float:left; clear:left;"><a href="tel:+49%20761%20203-67741">+49 761 203-67741 (secretary)</a></div><div class="TH-F4" style="float:left; clear:left;"><a href="/profile/hutter/#tppubs">Publications</a></div><div class="abcfslSocialIconsA" style="float:left; clear:left;"><a class="abcfslMR10" href="https://twitter.com/FrankRHutter" target="_blank" rel="noopener"><img decoding="async" src="http://ml.informatik.uni-freiburg.de/wp-content/plugins/staff-list/images/48-50/twitter.png" title="Twitter" alt="Twitter" itemprop="image" /></a><a class="abcfslMR10" href="https://scholar.google.de/citations?hl=de&user=YUrxwrkAAAAJ" target="_blank" rel="noopener"><img decoding="async" src="http://ml.informatik.uni-freiburg.de/wp-content/plugins/staff-list/images/48-50/googlescholar.png" title="GoogleScholar" alt="GoogleScholar" itemprop="image" /></a><a class="abcfslMR10" href="https://www.google.de/maps/place/48%C2%B000%2752.1%22N+7%C2%B049%2752.0%22E/@48.0144722,7.8311111,190m/data=!3m2!1e3!4b1!4m2!3m1!1s0x0:0x0" target="_blank" rel="noopener"><img decoding="async" src="http://ml.informatik.uni-freiburg.de/wp-content/plugins/staff-list/images/48-50/marker.png" title="Marker" alt="Marker" itemprop="image" /></a></div></div></div></div><div><div class="abcfslMT5 CE-F7"><p>I'm the Head of the Machine Learning Lab. I'm lucky enough to have an amazing team; all my Freiburg team members are linked in the menu on the top; Tübingen team members to come.</p> <p>I'm currently holding an ERC Consolidator Grant on <a href="https://www.automl.org/deep-learning-2-0-extending-the-power-of-deep-learning-to-the-meta-level/">Deep Learning 2.0 </a>and previously held ERC Starting and ERC PoC grants, as well as an Emmy Noether fellowship.</p> <h2>Information for students interested in projects, theses, or Hiwi positions</h2> <p>With machine learning being one of the hottest topic around, our small group is flooded with requests.<br /> To make the process efficient, please do not email me directly, but follow the instructions posted under <a href="https://ml.informatik.uni-freiburg.de/positions/">“working with us”</a>.</p> <h2>My position as Hector Endowed Fellow at the ELLIS Institute Tübingen</h2> <p>I'm on temporary leave at the <a href="https://institute-tue.ellis.eu/">ELLIS Institute Tübingen</a>. <span class="css-1jxf684 r-bcqeeo r-1ttztb7 r-qvutc0 r-poiln3">The ELLIS Institute is set to become a European Lighthouse of Machine Learning Excellence, and I’m thrilled to be part of it. Together with my new colleagues, and in close collaboration with my Freiburg team, I look forward to expanding my research on AutoML</span><span class="css-1jxf684 r-bcqeeo r-1ttztb7 r-qvutc0 r-poiln3"> in the most impactful way possible. I will continue to hire in Freiburg, but now I also have open positions in Tübingen. Next to the obvious positions in AutoML, I’m also looking for research engineers, postdocs and PhD students who are excited to build and would like to dive deep into large language models (pretraining, fine-tuning, and the connection of AutoML to both of these, as well as hosting open LLMs for Europe).</span></p> <h2>Commentary on AI risks</h2> <p>Our commentary on AI risks (with Yoshua Bengio, Geoff Hinton and ~20 other top AI researchers) <a href="http://www.science.org/doi/10.1126/science.adn0117">just got published in Science Magazine</a>. As the only European coauthor, I'd like to stress that I'm against more regulation in Europe; we already have enough of this. Instead, Europe needs to catch up on AI, by making dramatically higher investments (into basic research, startups and much more compute resources). We have an amazing <b>open source </b>community in Europe and we need to embrace it, rather than regulate it away. Open source is Europe‘s only hope to get out of the current deep technological dependence on the US. <span class="css-1jxf684 r-bcqeeo r-1ttztb7 r-qvutc0 r-poiln3">AI will shape the future of humanity, one way or the other, and we need to get this right. With so much at stake, AI needs to finally become a top strategic priority for Europe.<br /> </span></p> <p>For more on this commentary, please see my <a href="https://www.linkedin.com/in/frank-hutter-9190b24b/">LinkedIn post</a>.</p> <h2>Research focus</h2> <p>I focus on Automated Machine Learning (AutoML), an area in which I am proud to have a world leading group and to be <a href="https://scholar.google.com/citations?view_op=search_authors&hl=en&mauthors=label:automl">amongst the most cited researchers worldwide</a>. This includes research in the following areas, with some examples:</p> <ul> <li><strong>Efficient hyperparameter optimization (HPO)</strong> <ul> <li><a href="https://www.automl.org/automl/hpo-overview/">Bayesian optimization, multi-fidelity optimization, HPO benchmarks, Transfer HPO</a>. E.g., we won the <a href="https://bbochallenge.com/altleaderboard">2021 NeurIPS Blackbox optimization competition (warmstarting-friendly track)</a>.</li> </ul> </li> <li><strong>Neural architecture search (NAS)</strong> <ul> <li><a href="https://www.automl.org/nas-overview/">Speedup techniques for NAS by one-shot models, network morphisms, multi-fidelity optimization, and meta-learning; tabular & surrogate NAS benchmarks</a></li> </ul> </li> <li><strong>Meta-learning</strong> <ul> <li><a href="https://www.automl.org/meta-learning/">Learning to perform Bayesian inference, meta-learning for NAS + HPO, learning algorithm components, learning hyperparameter adaptation strategies</a></li> </ul> </li> <li><strong>AutoML systems</strong> <ul> <li><a href="https://www.automl.org/automl/autoweka/">Auto-WEKA</a>, <a href="https://www.automl.org/automl/auto-sklearn/">Auto-sklearn</a>, <a href="https://www.automl.org/automl/autopytorch/">Auto-PyTorch</a>. E.g., <a href="https://www.automl.org/blog-2nd-automl-challenge/">we won the first two international AutoML challenges by ChaLearn</a> with Auto-sklearn.</li> </ul> </li> <li><strong>Scientific experimentation</strong> <ul> <li>Making empirical research more reproducible and codifying human experts' strategies to the point where an autonomous system can execute them</li> </ul> </li> <li><strong>Auto-AI</strong> <ul> <li><a href="https://www.automl.org/automated-algorithm-design/algorithm-configuration/">Algorithm configuration</a>, <a href="https://www.automl.org/automated-algorithm-design/algorithm-selection/">algorithm selection</a> and <a href="https://www.automl.org/automated-algorithm-design/dac/">dynamic algorithm configuration</a>; we've won many SAT competitions and AI planning competitions with these Auto-AI techniques</li> </ul> </li> <li><strong>Explainable AutoML (xAutoML)</strong> <ul> <li>Performance prediction and automated algorithm analyses. Here’s a (dated) <a href="http://www.youtube.com/watch?v=bA-XwDStjng">Google tech talk I gave on Auto-AI + xAutoML</a></li> </ul> </li> </ul> <p>For more information on AutoML, please see <a href="https://www.automl.org/book/">our AutoML book</a> (the first book on AutoML) or our <a href="https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwii9fKTpsPzAhVG4qQKHZxSBPwQwqsBegQIBBAB&url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3D0eBR8a4MQ30&usg=AOvVaw3rsYvAhZj8JwKuw-7IbI9f">NeurIPS 2018 tutorial</a> (which had over 3000 attendees).</p> <p> </p> <p>Along the way, I've become a deep learner, with additional interests in</p> <ul> <li><strong>Architectures</strong>, <strong>optimizers</strong> and <strong>regularization methods</strong> <ul> <li><a href="https://www.automl.org/nas-overview/">Automatic architecture design</a></li> <li><a href="https://openreview.net/forum?id=Bkg6RiCqY7">Decoupled weight decay</a>, <a href="https://openreview.net/forum?id=Skq89Scxx">cosine annealing</a>, and <a href="https://openreview.net/forum?id=Skq89Scxx">SGD with restarts </a></li> <li><a href="https://arxiv.org/abs/2106.11189">Properly-tuned deep learning for SOTA performance on tabular data</a></li> </ul> </li> <li><strong>Uncertainty</strong> <ul> <li><a href="https://papers.nips.cc/paper/2016/hash/a96d3afec184766bfeca7a9f989fc7e7-Abstract.html">Bayesian optimization with Bayesian neural networks</a> (SG-MCMC)</li> <li><a href="https://arxiv.org/abs/2112.10510">Prior-data fitted networks (PFNs), an entirely new way to perform Bayesian inference via meta-learning with Transformers</a></li> </ul> </li> <li><strong>Applications</strong> of deep learning and AutoML <ul> <li>We were the <a href="https://onlinelibrary.wiley.com/doi/10.1002/hbm.23730">first to obtain competitive performance on EEG decoding with deep learning</a></li> <li>We <a href="https://openreview.net/forum?id=ByfyHh05tQ">dramatically improved RNA design using deep RL, meta-learning and joint NAS+HPO</a></li> <li>We were the <a href="https://arxiv.org/abs/2106.11189">first to achieve state-of-the-art performance on tabular data with deep learning, outperforming even properly-tuned gradient boosting</a>. This opens a huge part of data science to the benefits of modern deep learning.</li> </ul> </li> </ul> <p> </p> <h2>Affiliations</h2> <p>I'm a Hector-Endowed Fellow and PI at the <a href="https://institute-tue.ellis.eu/">ELLIS Institute Tübingen</a>, a member of the <a href="http://www.informatik.uni-freiburg.de/start_iif-en?set_language=en">Department of Computer Science</a> at the <a href="http://www.tf.uni-freiburg.de/">Faculty of Engineering</a> of the <a href="http://www.uni-freiburg.de/">University of Freiburg</a>, and head of the <a href="https://ellis.eu/units/freiburg">ELLIS unit Freiburg</a>. I hold an <a href="https://erc.europa.eu/funding/consolidator-grants">ERC Consolidator Grant</a> and previously held an <a href="https://erc.europa.eu/funding/starting-grants">ERC Starting Grant</a> and an <a href="https://erc.europa.eu/funding/proof-concept">ERC PoC Grant</a> from the European Research Council, as well as an <a href="https://www.dfg.de/en/research_funding/programmes/individual/emmy_noether/">Emmy Noether Grant</a> from the German Research Foundation (DFG). I'm a former member of the <a href="http://www.cs.ubc.ca/">Computer Science Department</a> of the <a href="http://www.ubc.ca/">University of British Columbia (UBC)</a>, specifically of the <a href="https://www.cs.ubc.ca/cs-research/lci">Laboratory for Computational Intelligence (LCI)</a> and the <a href="http://www.cs.ubc.ca/labs/beta/">Bioinformatics and Empirical & Theoretical Algorithmics Laboratory (BETA)</a>. In addition to my full-time role at the University of Freiburg, I also consulted for the <a href="https://www.bosch-ai.com/">Bosch Center for AI (BCAI)</a> as their Chief Expert for AutoML (2019-2023). I also was a machine learning consultant for <a href="https://www.zynga.com/">Zynga Inc</a> and am a co-founder of <a href="http://meta-algorithmics.com/">Meta-Algorithmic Technologies</a>. I earned my PhD at <a href="http://www.ubc.ca/">UBC</a> in 2009 and my Diplom (eq. MSc) at <a href="http://www.tu-darmstadt.de/index.en.jsp">Darmstadt University</a> in 2004.</p> <p>I was the inaugural general chair of the <a href="https://automl.cc">AutoML conference</a> in 2022 and 2023. I was program co-chair of <a href="https://ecmlpkdd2020.net/">ECML-PKDD 2020</a>. I co-founded and co-organized the <a href="https://www.automl.org/events/workshops/">ICML workshop series on AutoML</a> every year 2014 – 2021 (after which we turned it into the AutoML conference), the <a href="http://metalearning.ml/">NeurIPS workshop series on meta-learning</a>, and the <a href="https://www.automl.org/events/workshops/">Neural Architecture Search workshop at ICLR</a>. I also co-founded and regularly co-organized the <a href="https://bayesopt.github.io/">NeurIPS workshop series on Bayesian optimization</a>. Please see <a href="https://www.automl.org/workshops/">http://automl.org/workshops</a> for an up-to-date list of workshops I'm co-organizing.</p> <h2>Short bio</h2> <p>Frank Hutter is a Hector-Endowed Fellow and PI at the ELLIS Institute Tübingen, as well as Full Professor for Machine Learning at the University of Freiburg (Germany). Frank holds a PhD from the University of British Columbia (UBC, 2009) and a Diplom (eq. MSc) from TU Darmstadt (2004). He received the 2010 CAIAC doctoral dissertation award for the best thesis in AI in Canada, and with his coauthors, several best paper awards and prizes in international competitions on machine learning, SAT solving, and AI planning. He is a Fellow of EurAI and ELLIS, the director of the ELLIS unit Freiburg and the recipient of 3 ERC grants. Frank is best known for his research on automated machine learning (AutoML), including neural architecture search, efficient hyperparameter optimization, and meta-learning. He co-authored the first book on AutoML and the prominent AutoML tools Auto-WEKA, Auto-sklearn and Auto-PyTorch, won the first two AutoML challenges with his team, is co-teaching the first MOOC on AutoML, co-organized 15 AutoML-related workshops at ICML, NeurIPS and ICLR, and founded the AutoML conference as general chair in 2022 and 2023. In recent years, his focus has been on the intersection of foundation models and AutoML, including the first foundation model for tabular data, TabPFN, and improving pretraining and fine-tuning with AutoML.</p> </div><div class="SC-F6"><h2>Publications</h2><div class="teachpress_pub_list"><form name="tppublistform" method="get"><a name="tppubs" id="tppubs"></a></form><table class="teachpress_publication_list"><tr> <td> <h3 class="tp_h3" id="tp_h3_2025">2025</h3> </td> </tr><tr class="tp_publication tp_publication_conference"><td class="tp_pub_info"><p class="tp_pub_author"> Ferreira, Fabio; Rapant, Ivo; Franke, Jörg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2310.03940" title="arxiv" target="blank">Beyond Random Augmentations: Pretraining with Hard Views</a> <span class="tp_pub_type conference">Conference</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">The Thirteenth International Conference on Learning Representations (ICLR), </span><span class="tp_pub_additional_year">2025</span>.</p><div class="tp_bibtex" id="tp_bibtex_310" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('310','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@conference{ferreira-iclr25a,<br /> title = {Beyond Random Augmentations: Pretraining with Hard Views},<br /> author = {Fabio Ferreira and Ivo Rapant and Jörg K. H. Franke and Frank Hutter},<br /> year = {2025},<br /> booktitle = {The Thirteenth International Conference on Learning Representations (ICLR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_310" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2310.03940" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=AK1C55o4r7" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/pretraining-hard-views" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('310','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hollmann, Noah; Müller, Samuel; Purucker, Lennart; Krishnakumar, Arjun; Körfer, Max; Hoo, Shi Bin; Schirrmeister, Robin Tibor; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.nature.com/articles/s41586-024-08328-6" title="Nature Article" target="blank">Accurate predictions on small data with a tabular foundation model</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Nature, </span><span class="tp_pub_additional_volume">vol. 637, </span><span class="tp_pub_additional_issue">iss. 8045, </span><span class="tp_pub_additional_pages">pp. 319–326, </span><span class="tp_pub_additional_year">2025</span><span class="tp_pub_additional_note">, (<mark>Nature</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_402" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('402','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{Hollmann2025,<br /> title = {Accurate predictions on small data with a tabular foundation model},<br /> author = {Noah Hollmann and Samuel Müller and Lennart Purucker and Arjun Krishnakumar and Max Körfer and Shi Bin Hoo and Robin Tibor Schirrmeister and Frank Hutter },<br /> year = {2025},<br /> journal = {Nature},<br /> volume = {637},<br /> pages = {319–326},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_402" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.nature.com/articles/s41586-024-08328-6" title="Nature Article" target="_blank">Nature Article</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/PriorLabs/TabPFN" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('402','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2024">2024</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Ferreira, Fabio; Schlageter, Moreno; Rajan, Raghu; Biedenkapp, André; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2409.14084" title="arxiv" target="blank">One-shot World Models Using a Transformer Trained on a Synthetic Prior</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Workshop on Open-World Agents, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_373" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('373','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{ferreira-arxiv24a,<br /> title = {One-shot World Models Using a Transformer Trained on a Synthetic Prior},<br /> author = {Fabio Ferreira and Moreno Schlageter and Raghu Rajan and André Biedenkapp and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Workshop on Open-World Agents},<br /> journal = {arXiv:2409.14084 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_373" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2409.14084" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=nzTbSMbRtz" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/oswm" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('373','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Arango, Sebastian Pineda; Janowski, Maciej; Purucker, Lennart; Zela, Arber; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2410.19889" title="arXiv" target="blank">Ensembling Finetuned Language Models for Text Classification</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_385" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('385','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Arango2024c,<br /> title = {Ensembling Finetuned Language Models for Text Classification},<br /> author = {Sebastian Pineda Arango and Maciej Janowski and Lennart Purucker and Arber Zela and Frank Hutter and Josif Grabocka},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_385" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2410.19889" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=oeUE4Of8e8" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('385','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hoo, Shi Bin; Müller, Samuel; Salinas, David; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=H02X7RO3OC" title="OpenReview" target="blank">The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 TRL Workshop, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_391" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('391','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Hoo2024,<br /> title = {The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features},<br /> author = {Shi Bin Hoo and Samuel Müller and David Salinas and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 TRL Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_391" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=H02X7RO3OC" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('391','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feuer, Benjamin; Schirrmeister, Robin Tibor; Cherepanova, Valeriia; Hegde, Chinmay; Hutter, Frank; Goldblum, Micah; Cohen, Niv; White, Colin</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=FOfU3qhcIG" title="OpenReview" target="blank">TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">38th Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_392" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('392','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Feuer2024,<br /> title = {TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks},<br /> author = {Benjamin Feuer and Robin Tibor Schirrmeister and Valeriia Cherepanova and Chinmay Hegde and Frank Hutter and Micah Goldblum and Niv Cohen and Colin White},<br /> year = {2024},<br /> booktitle = {38th Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_392" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=FOfU3qhcIG" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('392','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Küken, Jaris; Purucker, Lennart; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2410.17787" title="arXiv" target="blank">Large Language Models Engineer Too Many Simple Features for Tabular Data</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Third Table Representation Learning Workshop, </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_382" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('382','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Küken2024,<br /> title = {Large Language Models Engineer Too Many Simple Features for Tabular Data},<br /> author = {Jaris Küken and Lennart Purucker and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Third Table Representation Learning Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_382" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2410.17787" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=xzEB47W6VS" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/llms_feature_engineering_bias" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('382','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Grazzi, Riccardo; Siems, Julien; Franke, Jörg K. H.; Zela, Arber; Hutter, Frank; Pontil, Massimiliano</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=EXGAodFkQX" title="OpenReview" target="blank">Unlocking State-Tracking in linear RNNs through Negative Eigenvalues</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning Workshop (M3L), </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_395" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('395','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Grazzi2024d,<br /> title = {Unlocking State-Tracking in linear RNNs through Negative Eigenvalues},<br /> author = {Riccardo Grazzi and Julien Siems and Jörg K. H. Franke and Arber Zela and Frank Hutter and Massimiliano Pontil},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning Workshop (M3L)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_395" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=EXGAodFkQX" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('395','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Bhethanabhotla, Sathya Kamesh; Swelam, Omar; Siems, Julien; Salinas, David; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2410.09385" title="arXiv" target="blank">Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 TSALM Workshop, </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Spotlight Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_387" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('387','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Bhethanabhotla2024,<br /> title = {Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models},<br /> author = {Sathya Kamesh Bhethanabhotla and Omar Swelam and Julien Siems and David Salinas and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 TSALM Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_387" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2410.09385" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=YBOQ5HnzI6" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/Mamba4Cast" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('387','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Andreas; Siems, Julien; Nori, Harsha; Salinas, David; Zela, Arber; Caruana, Rich; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2410.04560" title="arXiv" target="blank">GAMformer: Exploring In-Context Learning for Generalized Additive Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 TRL Workshop, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_390" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('390','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Müller2024,<br /> title = {GAMformer: Exploring In-Context Learning for Generalized Additive Models},<br /> author = {Andreas Müller and Julien Siems and Harsha Nori and David Salinas and Arber Zela and Rich Caruana and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 TRL Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_390" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2410.04560" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=W2CkzaqQnG" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('390','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Sukthanker, Rhea Sanjay; Staffler, Benedikt; Hutter, Frank; Klein, Aaron</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/pdf/2410.06479" title="arXiv" target="blank">Large Language Model Compression with Neural Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Workshop on Machine Learning and Compression, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_388" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('388','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Sukthanker2024c,<br /> title = {Large Language Model Compression with Neural Architecture Search},<br /> author = {Rhea Sanjay Sukthanker and Benedikt Staffler and Frank Hutter and Aaron Klein},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Workshop on Machine Learning and Compression},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_388" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/pdf/2410.06479" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('388','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Mallik, Neeratyoy; Janowski, Maciej; Hog, Johannes; Rakotoarison, Herilalaina; Klein, Aaron; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2411.07340" title="arXiv" target="blank">Warmstarting for Scaling Language Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2024 Workshop Adaptive Foundation Models, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_386" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('386','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Mallik2024,<br /> title = {Warmstarting for Scaling Language Models},<br /> author = {Neeratyoy Mallik and Maciej Janowski and Johannes Hog and Herilalaina Rakotoarison and Aaron Klein and Josif Grabocka and Frank Hutter},<br /> year = {2024},<br /> booktitle = {NeurIPS 2024 Workshop Adaptive Foundation Models},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_386" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2411.07340" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=2SilklW9NA" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('386','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg K. H.; Hefenbrock, Michael; Koehler, Gregor; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/2311.09058v3.pdf" title="Paper" target="blank">Improving Deep Learning Optimization through Constrained Parameter Regularization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">38th Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_332" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('332','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{franke2023constrained,<br /> title = {Improving Deep Learning Optimization through Constrained Parameter Regularization},<br /> author = {Jörg K. H. Franke and Michael Hefenbrock and Gregor Koehler and Frank Hutter},<br /> year = {2024},<br /> booktitle = {38th Conference on Neural Information Processing Systems (NeurIPS)},<br /> key = {2311.09058},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_332" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/2311.09058v3.pdf" title="Paper" target="_blank">Paper</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2311.09058v3" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/CPR" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('332','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Sukthanker, Rhea Sanjay; Zela, Arber; Staffler, Benedikt; Klein, Aaron; Purucker, Lennart; Franke, Joerg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2405.10299" title="arXiv" target="blank">HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">38th Conference on Neural Information Processing Systems (NeurIPS), DBT Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_394" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('394','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Sukthanker2024e,<br /> title = {HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models},<br /> author = {Rhea Sanjay Sukthanker and Arber Zela and Benedikt Staffler and Aaron Klein and Lennart Purucker and Joerg K.H. Franke and Frank Hutter},<br /> year = {2024},<br /> booktitle = {38th Conference on Neural Information Processing Systems (NeurIPS), DBT Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_394" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2405.10299" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/HW-GPT-Bench" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('394','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Helli, Kai; Schnurr, David; Hollmann, Noah; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=p3tSEFMwpG" title="OpenReview" target="blank">Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">38th Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_393" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('393','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Helli2024b,<br /> title = {Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data},<br /> author = {Kai Helli and David Schnurr and Noah Hollmann and Samuel Müller and Frank Hutter},<br /> year = {2024},<br /> booktitle = {38th Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_393" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=p3tSEFMwpG" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('393','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Strangmann, Tobias; Purucker, Lennart; Franke, Jörg K. H.; Rapant, Ivo; Ferreira, Fabio; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2411.01195" title="arxiv" target="blank">Transfer Learning for Finetuning Large Language Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle"> NeurIPS 2024 Workshop on Adaptive Foundation Models, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_384" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('384','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{strangmann-neuripsws24a,<br /> title = {Transfer Learning for Finetuning Large Language Models},<br /> author = {Tobias Strangmann and Lennart Purucker and Jörg K.H. Franke and Ivo Rapant and Fabio Ferreira and Frank Hutter},<br /> year = {2024},<br /> booktitle = { NeurIPS 2024 Workshop on Adaptive Foundation Models},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_384" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2411.01195" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('384','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Robertson, Jake; Schmidt, Thorsten; Hutter, Frank; Awad, Noor</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/AIES_2024_ManyFairHPO_to_upload.pdf" title="paper" target="blank">A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_381" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('381','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Robertson2024b,<br /> title = {A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes},<br /> author = { Jake Robertson and Thorsten Schmidt and Frank Hutter and Noor Awad},<br /> year = {2024},<br /> booktitle = {Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_381" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/AIES_2024_ManyFairHPO_to_upload.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/AIES_2024_ManyFairHPO_appendix.pdf" title="appendix" target="_blank">appendix</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/manyfairhpo-a-human-in-the-loop-fairness-aware-model-selection-framework-for-complex-fairness-objective-landscapes/" title="blog post" target="_blank">blog post</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/manyfairhpo_poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/jr2021/ManyFairHPO-AIES" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('381','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workingpaper"><td class="tp_pub_info"><p class="tp_pub_author"> Scheuer*, Dominik; Runge, Frederic*; Franke, Jörg K. H.; Wolfinger, Michael T.; Flamm, Christoph; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/kinPFN_biorxiv.pdf" title="paper" target="blank">KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks</a> <span class="tp_pub_type workingpaper">Working paper</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_380" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('380','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workingpaper{nokey,<br /> title = {KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks},<br /> author = {Dominik Scheuer* and Frederic* Runge and Jörg K.H. Franke and Michael T. Wolfinger and Christoph Flamm and Frank Hutter},<br /> year = {2024},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_380" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/kinPFN_biorxiv.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.1101/2024.10.15.618378" title="bioRxiv" target="_blank">bioRxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('380','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Arango, Sebastian Pineda; Janowski, Maciej; Purucker, Lennart; Zela, Arber; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2410.04520" title="arXiv" target="blank">Dynamic Post-Hoc Neural Ensemblers</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Preprint, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_383" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('383','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Arango2024b,<br /> title = {Dynamic Post-Hoc Neural Ensemblers},<br /> author = {Sebastian Pineda Arango and Maciej Janowski and Lennart Purucker and Arber Zela and Frank Hutter and Josif Grabocka},<br /> year = {2024},<br /> booktitle = {Preprint},<br /> journal = {Preprint arXiv},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_383" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2410.04520" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('383','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inbook"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1007/978-1-0716-4079-1_5" title="Machine Learning for RNA Design: LEARNA" target="blank">Machine Learning for RNA Design: LEARNA</a> <span class="tp_pub_type inbook">Book Chapter</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Churkin, Alexander; Barash, Danny (Ed.): <span class="tp_pub_additional_booktitle">RNA Design: Methods and Protocols, </span><span class="tp_pub_additional_chapter"> Chapter 5, </span><span class="tp_pub_additional_pages">pp. 63–93, </span><span class="tp_pub_additional_publisher">Springer US, </span><span class="tp_pub_additional_address">New York, NY, </span><span class="tp_pub_additional_edition">1, </span><span class="tp_pub_additional_year">2024</span>, <span class="tp_pub_additional_isbn">ISBN: 978-1-0716-4079-1</span>.</p><div class="tp_bibtex" id="tp_bibtex_379" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('379','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inbook{nokey,<br /> title = {Machine Learning for RNA Design: LEARNA},<br /> author = {Frederic Runge and Frank Hutter},<br /> editor = {Alexander Churkin and Danny Barash},<br /> doi = {10.1007/978-1-0716-4079-1_5},<br /> year = {2024},<br /> isbn = {978-1-0716-4079-1},<br /> booktitle = {RNA Design: Methods and Protocols},<br /> pages = {63--93},<br /> publisher = {Springer US},<br /> address = {New York, NY},<br /> edition = {1},<br /> chapter = {5},<br /> series = {Methods in Molecular Biology},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_379" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.1007/978-1-0716-4079-1_5" title="chapter" target="_blank">chapter</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1007/978-1-0716-4079-1_5" title="Follow DOI:10.1007/978-1-0716-4079-1_5" target="_blank">doi:10.1007/978-1-0716-4079-1_5</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('379','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Arango, Sebastian Pineda; Biedenkapp, André; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=MlB61zPAeR" title="OpenReview" target="blank">HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Runner up for the <a href="https://2024.automl.cc/?page_id=1406">best paper award</a></mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_345" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('345','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala-automl24a,<br /> title = {HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning},<br /> author = {Gresa Shala and Sebastian Pineda Arango and André Biedenkapp and Frank Hutter and Josif Grabocka},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_345" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=MlB61zPAeR" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/releaunifreiburg/HPO-RL-Bench" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('345','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Sukthanker, Rhea Sanjay; Krishnakumar, Arjun; Safari, Mahmoud; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=4klsxqPerv" title="OpenReview" target="blank">Weight-Entanglement Meets Gradient-Based Neural Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_359" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('359','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Sukthanker2024b,<br /> title = {Weight-Entanglement Meets Gradient-Based Neural Architecture Search},<br /> author = {Rhea Sanjay Sukthanker and Arjun Krishnakumar and Mahmoud Safari and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_359" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=4klsxqPerv" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('359','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Grazzi, Riccardo; Siems, Julien; Schrodi, Simon; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=rJhOG0P8nr" title="OpenReview" target="blank">Is Mamba Capable of In-Context Learning?</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_360" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('360','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Grazzi2024b,<br /> title = {Is Mamba Capable of In-Context Learning?},<br /> author = {Riccardo Grazzi and Julien Siems and Simon Schrodi and Thomas Brox and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_360" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=rJhOG0P8nr" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('360','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Strack, Lukas; Safari, Mahmoud; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=GDSrWrDYW3" title="OpenReview" target="blank">Towards Efficient Search for Customized Activation Functions With Gradient Descent</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_362" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('362','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Strack2024,<br /> title = {Towards Efficient Search for Customized Activation Functions With Gradient Descent},<br /> author = {Lukas Strack and Mahmoud Safari and Frank Hutter },<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_362" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=GDSrWrDYW3" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('362','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Karakasli, Goktug; Adriaensen, Steven; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=5Lm2ghxMlp" title="OpenReview" target="blank">NOSBench-101: Towards Reproducible Neural Optimizer Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_364" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('364','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Karakasli2024,<br /> title = {NOSBench-101: Towards Reproducible Neural Optimizer Search},<br /> author = {Goktug Karakasli and Steven Adriaensen and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_364" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=5Lm2ghxMlp" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('364','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Rapant, Ivo; Purucker, Lennart; Ferreira, Fabio; Arango, Sebastian Pineda; Kadra, Arlind; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=d0Hapti3Uc" title="OpenReview" target="blank">Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_357" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('357','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Rapant2024b,<br /> title = {Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models},<br /> author = {Ivo Rapant and Lennart Purucker and Fabio Ferreira and Sebastian Pineda Arango and Arlind Kadra and Josif Grabocka and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_357" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=d0Hapti3Uc" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/QTT" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('357','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Krishnakumar, Arjun; Jha, Abhash Kumar; Moradian, Shakiba; Rapp, Martin; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=YNyTumD0U9" title="OpenReview" target="blank">LoRA-DARTS: Low Rank Adaptation for Differentiable Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_368" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('368','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Krishnakumar2024,<br /> title = {LoRA-DARTS: Low Rank Adaptation for Differentiable Architecture Search},<br /> author = {Arjun Krishnakumar and Abhash Kumar Jha and Shakiba Moradian and Martin Rapp and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_368" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=YNyTumD0U9" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('368','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Viering, Tom Julian; Adriaensen, Steven; Rakotoarison, Herilalaina; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=neEKHQDTHV" title="OpenReview" target="blank">From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_370" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('370','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Viering2024,<br /> title = {From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks},<br /> author = {Tom Julian Viering and Steven Adriaensen and Herilalaina Rakotoarison and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_370" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=neEKHQDTHV" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('370','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Birinxhiku, Lum; Stoll, Danny; Schrodi, Simon; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=gze7ISazsz" title="OpenReview" target="blank">Beyond Graph-Based Modeling for Hierarchical Neural Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_371" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('371','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Birinxhiku2024,<br /> title = {Beyond Graph-Based Modeling for Hierarchical Neural Architecture Search},<br /> author = {Lum Birinxhiku and Danny Stoll and Simon Schrodi and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_371" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=gze7ISazsz" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('371','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Blauth, Simon; Bürger, Tobias; Häringer, Zacharias; Franke, Jörg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=VpYJPNKSqs" title="OpenReview" target="blank">Fast Optimizer Benchmark</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_372" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('372','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Blauth2024,<br /> title = {Fast Optimizer Benchmark},<br /> author = {Simon Blauth and Tobias Bürger and Zacharias Häringer and Jörg K.H. Franke and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_372" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=VpYJPNKSqs" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('372','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Helli, Kai; Schnurr, David; Hollmann, Noah; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=VbmqcoHpGT" title="OpenReview" target="blank">Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_365" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('365','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Helli2024,<br /> title = {Drift-Resilient TabPFN: In-Context Learning Distribution Shifts on Tabular Data},<br /> author = {Kai Helli and David Schnurr and Noah Hollmann and Samuel Müller and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_365" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=VbmqcoHpGT" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('365','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_conference"><td class="tp_pub_info"><p class="tp_pub_author"> Robertson, Jake; Hollmann, Noah; Awad, Noor; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2407.05732v1" title="Arxiv" target="blank">FairPFN: Transformers Can do Counterfactual Fairness</a> <span class="tp_pub_type conference">Conference</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_354" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('354','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@conference{Robertson2024,<br /> title = {FairPFN: Transformers Can do Counterfactual Fairness},<br /> author = {Jake Robertson and Noah Hollmann and Noor Awad and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_354" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2407.05732v1" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=NkTgoMlKKi" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('354','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Rakotoarison, Herilalaina; Adriaensen, Steven; Mallik, Neeratyoy; Garibov, Samir; Bergman, Edward; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=TPwrOQhyRj" title="OpenReview" target="blank">In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_369" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('369','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Rakotoarison2024,<br /> title = {In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization},<br /> author = {Herilalaina Rakotoarison and Steven Adriaensen and Neeratyoy Mallik and Samir Garibov and Edward Bergman and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_369" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=TPwrOQhyRj" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('369','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Geburek, Anton Merlin; Mallik, Neeratyoy; Stoll, Danny; Bouthillier, Xavier; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=AAASG6BNvl" title="OpenReview" target="blank">LMEMs for post-hoc analysis of HPO Benchmarking</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_363" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('363','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Geburek2024,<br /> title = {LMEMs for post-hoc analysis of HPO Benchmarking},<br /> author = {Anton Merlin Geburek and Neeratyoy Mallik and Danny Stoll and Xavier Bouthillier and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_363" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=AAASG6BNvl" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('363','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Mallik, Neeratyoy; Bergman, Edward; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2403.01888" title="Arxiv" target="blank">Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_349" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('349','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Watanabe2024,<br /> title = {Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks},<br /> author = {Shuhei Watanabe and Neeratyoy Mallik and Edward Bergman and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), ABCD Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_349" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2403.01888" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=uisnH6jUDz" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('349','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Bergman, Eddie; Purucker, Lennart; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2405.03389" title="arXiv" target="blank">Don’t Waste Your Time: Early Stopping Cross-Validation</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_350" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('350','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Bergman2024,<br /> title = {Don’t Waste Your Time: Early Stopping Cross-Validation},<br /> author = {Eddie Bergman and Lennart Purucker and Frank Hutter },<br /> year = {2024},<br /> booktitle = {Proceedings of the Third International Conference on Automated Machine Learning (AutoML 2024), Methods Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_350" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2405.03389" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=D8IFbV2rTP" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/DontWasteYourTime-early-stopping" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('350','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_conference"><td class="tp_pub_info"><p class="tp_pub_author"> Patil, Sharat; Schirrmeister, Robin Tibor; Ball, Tonio; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=RlYWwZXlsJ" title="OpenReview" target="blank">CoordConformer: Heterogenous EEG datasets decoding using Transformers</a> <span class="tp_pub_type conference">Conference</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM@ICML), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_353" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('353','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@conference{Patil2024,<br /> title = {CoordConformer: Heterogenous EEG datasets decoding using Transformers},<br /> author = {Sharat Patil and Robin Tibor Schirrmeister and Tonio Ball and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM@ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_353" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=RlYWwZXlsJ" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('353','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_conference"><td class="tp_pub_info"><p class="tp_pub_author"> Sukthanker, Rhea Sanjay; Zela, Arber; Staffler, Benedikt; Dooley, Samuel; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=l6COqSWzi9" title="OpenReview" target="blank">Multi-objective Differentiable Neural Architecture Search</a> <span class="tp_pub_type conference">Conference</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">2nd Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_352" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('352','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@conference{Sukthanker2024,<br /> title = {Multi-objective Differentiable Neural Architecture Search},<br /> author = {Rhea Sanjay Sukthanker and Arber Zela and Benedikt Staffler and Samuel Dooley and Josif Grabocka and Frank Hutter},<br /> year = {2024},<br /> booktitle = {2nd Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization (WANT@ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_352" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=l6COqSWzi9" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('352','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Kadlecová, Gabriela; Lukasik, Jovita; Pilát, Martin; Vidnerová, Petra; Safari, Mahmoud; Neruda, Roman; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2404.16551" title="ArXiv" target="blank">Surprisingly Strong Performance Prediction with Neural Graph Features</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 41st International Conference on Machine Learning (ICML), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_346" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('346','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{kadlecova-icml24a,<br /> title = {Surprisingly Strong Performance Prediction with Neural Graph Features},<br /> author = {Gabriela Kadlecová and Jovita Lukasik and Martin Pilát and Petra Vidnerová and Mahmoud Safari and Roman Neruda and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_346" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2404.16551" title="ArXiv" target="_blank">ArXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=EhPpZV6KLk" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/gabikadlecova/zc_combine" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('346','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Rakotoarison, Herilalaina; Adriaensen, Steven; Mallik, Neeratyoy; Garibov, Samir; Bergman, Eddie; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2404.16795" title="Arxiv" target="blank">In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 41st International Conference on Machine Learning (ICML), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_347" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('347','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{nokey,<br /> title = {In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization},<br /> author = {Herilalaina Rakotoarison and Steven Adriaensen and Neeratyoy Mallik and Samir Garibov and Eddie Bergman and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_347" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2404.16795" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=VyoY3Wh9Wd" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/ifBO" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('347','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, Marius; Karl, Florian; Klier, Anne; Moosbauer, Julia; Tornede, Alexander; Mueller, Andreas C; Hutter, Frank; Feurer, Matthias; Bischl, Bernd</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2406.03348" title="Arxiv" target="blank">Position: A Call to Action for a Human-Centered AutoML Paradigm</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 41st International Conference on Machine Learning (ICML), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_348" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('348','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Lindauer2024,<br /> title = {Position: A Call to Action for a Human-Centered AutoML Paradigm},<br /> author = {Marius Lindauer and Florian Karl and Anne Klier and Julia Moosbauer and Alexander Tornede and Andreas C Mueller and Frank Hutter and Matthias Feurer and Bernd Bischl},<br /> year = {2024},<br /> booktitle = {Proceedings of the 41st International Conference on Machine Learning (ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_348" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2406.03348" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=wELbEYgnmo" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('348','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Franke, Jörg K. H.; Fertmann, Daniel; Backofen, Rolf; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.1093/bioinformatics/btae222" title="Partial RNA Design" target="blank">Partial RNA Design</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Bioinformatics, </span><span class="tp_pub_additional_volume">vol. 40, </span><span class="tp_pub_additional_number">no. Supplement_1, </span><span class="tp_pub_additional_pages">pp. i437–i445, </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation at ISMB'24</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_375" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('375','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{nokey,<br /> title = {Partial RNA Design},<br /> author = {Frederic Runge and Jörg K.H. Franke and Daniel Fertmann and Rolf Backofen and Frank Hutter},<br /> doi = {https://doi.org/10.1093/bioinformatics/btae222},<br /> year = {2024},<br /> journal = {Bioinformatics},<br /> volume = {40},<br /> number = {Supplement_1},<br /> pages = {i437--i445},<br /> publisher = {Oxford University Press},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_375" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://academic.oup.com/bioinformatics/article/40/Supplement_1/i437/7700895" title="publication" target="_blank">publication</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.1093/bioinformatics/btae222" title="Follow DOI:https://doi.org/10.1093/bioinformatics/btae222" target="_blank">doi:https://doi.org/10.1093/bioinformatics/btae222</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('375','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Patil, Sharat; Runge, Frederic; Franke, Jörg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.biorxiv.org/content/10.1101/2024.03.09.584209v1.full.pdf" title="bioRxiv" target="blank">Towards Generative RNA Design with Tertiary Interactions</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024), </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_341" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('341','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{nokey,<br /> title = {Towards Generative RNA Design with Tertiary Interactions},<br /> author = {Sharat Patil and Frederic Runge and Jörg K. H. Franke and Frank Hutter},<br /> year = {2024},<br /> booktitle = {The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_341" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://www.biorxiv.org/content/10.1101/2024.03.09.584209v1.full.pdf" title="bioRxiv" target="_blank">bioRxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('341','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Matus, Dominika; Runge, Frederic; Franke, Jörg K. H.; Gerne, Lars; Uhl, Michael; Hutter, Frank; Backofen, Rolf</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/03/2024_ICLR_GEM_RPI-1.pdf" title="preprint" target="blank">RNA-Protein Interaction Prediction via Sequence Embeddings</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_340" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('340','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{nokey,<br /> title = {RNA-Protein Interaction Prediction via Sequence Embeddings},<br /> author = {Dominika Matus and Frederic Runge and Jörg K. H. Franke and Lars Gerne and Michael Uhl and Frank Hutter and Rolf Backofen},<br /> year = {2024},<br /> booktitle = {The Generative and Experimental perspectives in bioMolecular design (GEM) workshop (ICLR 2024)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_340" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/03/2024_ICLR_GEM_RPI-1.pdf" title="preprint" target="_blank">preprint</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('340','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Kohli, Ravin; Feurer, Matthias; Eggensperger, Katharina; Bischl, Bernd; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/04/61_towards_quantifying_the_effect.pdf" title="preprint" target="blank">Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_342" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('342','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Kohli2024,<br /> title = {Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning},<br /> author = {Ravin Kohli and Matthias Feurer and Katharina Eggensperger and Bernd Bischl and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Data-centric Machine Learning Research (DMLR) Workshop (ICLR 2024)},<br /> journal = {Data-centric Machine Learning Research (DMLR) Workshop at ICLR},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_342" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/04/61_towards_quantifying_the_effect.pdf" title="preprint" target="_blank">preprint</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('342','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg; Hefenbrock, Michael; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=XoWtroECJU&noteId=8ouEb8oPgO" title="OpenReview" target="blank">Preserving Principal Subspaces to Reduce Catastrophic Forgetting in Fine-tuning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_343" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('343','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{nokey,<br /> title = {Preserving Principal Subspaces to Reduce Catastrophic Forgetting in Fine-tuning},<br /> author = {Jörg Franke and Michael Hefenbrock and Frank Hutter},<br /> year = {2024},<br /> booktitle = {Mathematical and Empirical Understanding of Foundation Models<br /> (ME-FoMo) Workshop},<br /> journal = {Workshop on Mathematical and Empirical Understanding of Foundation Models (ME-FoMo)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_343" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=XoWtroECJU&noteId=8ouEb8oPgO" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('343','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Grazzi, Riccardo; Siems, Julien; Schrodi, Simon; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2402.03170" title="Arxiv" target="blank">Is Mamba Capable of In-Context Learning?</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_339" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('339','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Grazzi2024,<br /> title = {Is Mamba Capable of In-Context Learning?},<br /> author = {Riccardo Grazzi and Julien Siems and Simon Schrodi and Thomas Brox and Frank Hutter },<br /> year = {2024},<br /> booktitle = {Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_339" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2402.03170" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('339','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg K. H.; Runge, Frederic; Köksal, Ryan; Backofen, Rolf; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/rnaformer_biorxiv.pdf" title="paper" target="blank">RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_378" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('378','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{nokey,<br /> title = {RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction},<br /> author = {Jörg K.H. Franke and Frederic Runge and Ryan Köksal and Rolf Backofen and Frank Hutter},<br /> year = {2024},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_378" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/rnaformer_biorxiv.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.1101/2024.02.12.579881" title="bioRxiv" target="_blank">bioRxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('378','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=NjU0jtXcYn" title="OpenReview" target="blank">A General Framework for User-Guided Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">The Twelfth International Conference on Learning Representations (ICLR), </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_336" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('336','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Hvarfner2024,<br /> title = {A General Framework for User-Guided Bayesian Optimization},<br /> author = {Carl Hvarfner and Frank Hutter and Luigi Nardi},<br /> year = {2024},<br /> booktitle = {The Twelfth International Conference on Learning Representations (ICLR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_336" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=NjU0jtXcYn" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('336','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Arango, Sebastian Pineda; Ferreira, Fabio; Kadra, Arlind; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=tqh1zdXIra" title="OpenReview" target="blank">Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">The Twelfth International Conference on Learning Representations (ICLR), </span><span class="tp_pub_additional_year">2024</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_337" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('337','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Arango2024,<br /> title = {Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How},<br /> author = {Sebastian Pineda Arango and Fabio Ferreira and Arlind Kadra and Frank Hutter and Josif Grabocka},<br /> year = {2024},<br /> booktitle = {The Twelfth International Conference on Learning Representations (ICLR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_337" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=tqh1zdXIra" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('337','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Farid, Karim; Franke, Jörg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/rnabench.pdf" title="paper" target="blank">RNABench: A Comprehensive Library for In Silico RNA Modelling</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_377" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('377','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{nokey,<br /> title = {RNABench: A Comprehensive Library for In Silico RNA Modelling},<br /> author = {Frederic Runge and Karim Farid and Jörg K.H. Franke and Frank Hutter},<br /> year = {2024},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_377" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/rnabench.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.1101/2024.01.09.574794" title="bioRxiv" target="_blank">bioRxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('377','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Bergman, Edward; Feurer, Matthias; Bahram, Aron; Balef, Amir Rezaei; Purucker, Lennart; Segel, Sarah; Lindauer, Marius; Hutter, Frank; Eggensperger, Katharina</p><p class="tp_pub_title"><a class="tp_title_link" href="https://joss.theoj.org/papers/10.21105/joss.06367" title="JOSS" target="blank">AMLTK: A Modular AutoML Toolkit in Python</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Open Source Software, </span><span class="tp_pub_additional_volume">vol. 9, </span><span class="tp_pub_additional_number">no. 100, </span><span class="tp_pub_additional_pages">pp. 6367, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_355" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('355','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{bergman2024amltk,<br /> title = {AMLTK: A Modular AutoML Toolkit in Python},<br /> author = {Edward Bergman and Matthias Feurer and Aron Bahram and Amir Rezaei Balef and Lennart Purucker and Sarah Segel and Marius Lindauer and Frank Hutter and Katharina Eggensperger},<br /> year = {2024},<br /> journal = {Journal of Open Source Software},<br /> volume = {9},<br /> number = {100},<br /> pages = {6367},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_355" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://joss.theoj.org/papers/10.21105/joss.06367" title="JOSS" target="_blank">JOSS</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/amltk" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('355','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Pfefferle, Alexander; Purucker, Lennart; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=PObXviy706" title="https://openreview.net/forum?id=PObXviy706" target="blank">DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">CVPR 2024: Segment Anything In Medical Images On Laptop, </span><span class="tp_pub_additional_year">2024</span>.</p><div class="tp_bibtex" id="tp_bibtex_396" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('396','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{<LineBreak>pfefferle2024daft,<br /> title = {DAFT: Data-Aware Fine-Tuning of Foundation Models for Efficient and Effective Medical Image Segmentation},<br /> author = {Alexander Pfefferle and Lennart Purucker and Frank Hutter},<br /> year = {2024},<br /> booktitle = {CVPR 2024: Segment Anything In Medical Images On Laptop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_396" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=PObXviy706" title="https://openreview.net/forum?id=PObXviy706" target="_blank">https://openreview.net/forum?id=PObXviy706</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('396','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2023">2023</h3> </td> </tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Franke, Jörg K. H.; Fertmann, Daniel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2023/12/2023_mlsb_workshop_wl4rna.pdf" title="publication" target="blank">Rethinking Performance Measures of RNA Secondary Structure Problems</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">Machine Learning for Structural Biology Workshop, (NeruIPS 2023), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_333" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('333','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{runge2023rethinking,<br /> title = {Rethinking Performance Measures of RNA Secondary Structure Problems},<br /> author = {Frederic Runge and Jörg K. H. Franke and Daniel Fertmann and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Machine Learning for Structural Biology Workshop, (NeruIPS 2023)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_333" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2023/12/2023_mlsb_workshop_wl4rna.pdf" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('333','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg K. H.; Hefenbrock, Michael; Koehler, Gregor; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2023/12/2023_NeurIPS_OPT_Workshop_New_Horizons_in_Parameter_Regularization.pdf" title="publication" target="blank">New Horizons in Parameter Regularization: A Constraint Approach</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">OPT2023: 15th Annual Workshop on Optimization for Machine Learning, (NeurIPS 2023), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_331" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('331','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{franke2023new,<br /> title = {New Horizons in Parameter Regularization: A Constraint Approach},<br /> author = {Jörg K. H. Franke and Michael Hefenbrock and Gregor Koehler and Frank Hutter},<br /> year = {2023},<br /> booktitle = {OPT2023: 15th Annual Workshop on Optimization for Machine Learning, (NeurIPS 2023)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_331" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2023/12/2023_NeurIPS_OPT_Workshop_New_Horizons_in_Parameter_Regularization.pdf" title="publication" target="_blank">publication</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://opt-ml.org/" title="workshop" target="_blank">workshop</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('331','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Schrodi, Simon; Stoll, Danny; Ru, Binxin; Sukthanker, Rhea Sanjay; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=Hpt1i5j6wh" title="OpenReview" target="blank">Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_314" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('314','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{schrodi2023hierarchical,<br /> title = {Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars},<br /> author = {Simon Schrodi and Danny Stoll and Binxin Ru and Rhea Sanjay Sukthanker and Thomas Brox and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_314" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=Hpt1i5j6wh" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('314','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hollmann, Noah; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=9WSxQZ9mG7" title="OpenReview" target="blank">Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_317" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('317','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{hollmann2023caafe,<br /> title = {Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering},<br /> author = {Noah Hollmann and Samuel Müller and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_317" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=9WSxQZ9mG7" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('317','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Dooley*, Samuel; Sukthanker*, Rhea Sanjay; Dickerson, John P; White, Colin; Hutter, Frank; Goldblum, Micah</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=1vzF4zWQ1E" title="OpenReview" target="blank">Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span><span class="tp_pub_additional_note">, (<mark>Oral Paper - top 2% of accepted papers</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_313" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('313','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{dooley-fairnas-2023,<br /> title = {Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition},<br /> author = {Samuel Dooley* and Rhea Sanjay Sukthanker* and John P Dickerson and Colin White and Frank Hutter and Micah Goldblum},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_313" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=1vzF4zWQ1E" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('313','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Hellsten, Erik Orm; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=dX9MjUtP1A" title="OpenReview" target="blank">Self-Correcting Bayesian Optimization through Bayesian Active Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_312" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('312','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{<LineBreak>hvarfner2023selfcorrecting,<br /> title = {Self-Correcting Bayesian Optimization through Bayesian Active Learning},<br /> author = {Carl Hvarfner and Erik Orm Hellsten and Frank Hutter and Luigi Nardi},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_312" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=dX9MjUtP1A" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('312','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Mallik, Neeratyoy; Bergman, Eddie; Hvarfner, Carl; Stoll, Danny; Janowski, Maciej; Lindauer, Marius; Nardi, Luigi; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=uoiwugtpCH" title="OpenReview" target="blank">PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_315" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('315','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mallik2023priorband,<br /> title = {PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning},<br /> author = {Neeratyoy Mallik and Eddie Bergman and Carl Hvarfner and Danny Stoll and Maciej Janowski and Marius Lindauer and Luigi Nardi and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_315" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=uoiwugtpCH" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('315','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Adriaensen, Steven; Rakotoarison, Herilalaina; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=xgTV6rmH6n" title="OpenReview" target="blank">Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_316" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('316','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{adriaensen2023lcpfn,<br /> title = {Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks},<br /> author = {Steven Adriaensen and Herilalaina Rakotoarison and Samuel Müller and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_316" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=xgTV6rmH6n" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('316','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/486" title="c-TPE: Tree-Structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization" target="blank">c-TPE: Tree-Structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), </span><span class="tp_pub_additional_publisher">ijcai.org, </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_307" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('307','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{watanabe-ijcai23-ctpe,<br /> title = {c-TPE: Tree-Structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization},<br /> author = {Shuhei Watanabe and Frank Hutter},<br /> doi = {https://doi.org/10.24963/ijcai.2023/486},<br /> year = {2023},<br /> booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23)},<br /> journal = {IJCAI},<br /> publisher = {ijcai.org},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_307" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2211.14411" title="ArXiv" target="_blank">ArXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/nabenabe0928/constrained-tpe" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/1Y9UZYhVmX65tqr6DGYOpzKmQL2x-wRPW/view" title="slides" target="_blank">slides</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/15eY1VjuzXwrNU3HTT1xVmzG8l3XYaqyR/view" title="poster" target="_blank">poster</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://recorder-v3.slideslive.com/#/share?share=85105&s=6efc3812-eff8-4ea2-94fb-9dc9e4ba82b9" title="video" target="_blank">video</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/486" title="Follow DOI:https://doi.org/10.24963/ijcai.2023/486" target="_blank">doi:https://doi.org/10.24963/ijcai.2023/486</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('307','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Awad, Noor; Onishi, Masaki; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/487" title="Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator" target="blank">Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_308" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('308','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Watanabe22b,<br /> title = {Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator},<br /> author = {Shuhei Watanabe and Noor Awad and Masaki Onishi and Frank Hutter},<br /> doi = {https://doi.org/10.24963/ijcai.2023/487},<br /> year = {2023},<br /> booktitle = {Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_308" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2212.06751" title="arXiv " target="_blank">arXiv </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/nabenabe0928/meta-learn-tpe" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/1hIhKlrxF-Deq_DgMiOjBMambK7sDZpIP/view" title="slides" target="_blank">slides</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/1l2Na0UaT7SKZkmSVi6ljGcY1AuH-8sZK/view" title="poster" target="_blank">poster</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://recorder-v3.slideslive.com/#/share?share=85157&s=055efc27-22d7-4b0d-b17c-67dbb78a88a9" title="video" target="_blank">video</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/487" title="Follow DOI:https://doi.org/10.24963/ijcai.2023/487" target="_blank">doi:https://doi.org/10.24963/ijcai.2023/487</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('308','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Bansal, Archit; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/488" title="PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces" target="blank">PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_309" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('309','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Watanabe23c,<br /> title = {PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces},<br /> author = {Shuhei Watanabe and Archit Bansal and Frank Hutter},<br /> doi = {https://doi.org/10.24963/ijcai.2023/488},<br /> year = {2023},<br /> booktitle = {Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI'23)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_309" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2304.10255" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/nabenabe0928/local-anova" title="GitHub" target="_blank">GitHub</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/1pwCa0fgh6jIooW0admOmkApa8VQqAgTF/view" title="slides" target="_blank">slides</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/18MvL9BtqFcnS6CkcOOHg_GglsTLoxdX8/view" title="poster" target="_blank">poster</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://recorder-v3.slideslive.com/#/share?share=85189&s=65a4587d-60b8-46c9-9e46-a75339ba8495" title="video" target="_blank">video</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.24963/ijcai.2023/488" title="Follow DOI:https://doi.org/10.24963/ijcai.2023/488" target="_blank">doi:https://doi.org/10.24963/ijcai.2023/488</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('309','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Franke, Jörg K. H.; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://icml-compbio.github.io/2023/papers/WCBICML2023_paper42.pdf" title="publication" target="blank">Towards Automated Design of Riboswitches</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">The 2023 ICML Workshop on Computational Biology, </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_334" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('334','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{runge2023towards,<br /> title = {Towards Automated Design of Riboswitches},<br /> author = {Frederic Runge and Jörg K. H. Franke and Frank Hutter},<br /> year = {2023},<br /> booktitle = {The 2023 ICML Workshop on Computational Biology},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_334" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://icml-compbio.github.io/2023/papers/WCBICML2023_paper42.pdf" title="publication" target="_blank">publication</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2307.08801" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('334','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Samuel; Feurer, Matthias; Hollmann, Noah; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=1DP5fR3iTr" title="OpenReview" target="blank">PFNs4BO: In-Context Learning for Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 40th International Conference on Machine Learning (ICML 2023), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_302" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('302','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{sam_at_icml23,<br /> title = {PFNs4BO: In-Context Learning for Bayesian Optimization},<br /> author = {Samuel Müller and Matthias Feurer and Noah Hollmann and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Proceedings of the 40th International Conference on Machine Learning (ICML 2023)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_302" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=1DP5fR3iTr" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('302','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg K. H.; Runge, Frederic; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/scalable_dl_for_rna_secondary_structure_prediction.pdf" title="paper" target="blank">Scalable Deep Learning for RNA Secondary Structure Prediction</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">The 2023 ICML Workshop on Computational Biology, </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_376" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('376','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{nokey,<br /> title = {Scalable Deep Learning for RNA Secondary Structure Prediction},<br /> author = {Jörg K.H. Franke and Frederic Runge and Frank Hutter},<br /> year = {2023},<br /> booktitle = {The 2023 ICML Workshop on Computational Biology},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_376" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/scalable_dl_for_rna_secondary_structure_prediction.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.48550/arXiv.2307.10073" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('376','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Rajan, Raghu; Diaz, Jessica Lizeth Borja; Guttikonda, Suresh; Ferreira, Fabio; Biedenkapp, André; von Hartz, Jan Ole; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1613/jair.1.14314" title="MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning" target="blank">MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research (JAIR), </span><span class="tp_pub_additional_volume">vol. 77, </span><span class="tp_pub_additional_pages">pp. 821-890, </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_304" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('304','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{rajan-jair23,<br /> title = {MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning},<br /> author = {Raghu Rajan and Jessica Lizeth Borja Diaz and Suresh Guttikonda and Fabio Ferreira and André Biedenkapp and Jan Ole von Hartz and Frank Hutter},<br /> doi = {10.1613/jair.1.14314},<br /> year = {2023},<br /> journal = {Journal of Artificial Intelligence Research (JAIR)},<br /> volume = {77},<br /> pages = {821-890},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_304" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jair.org/index.php/jair/article/view/14314" title="publication" target="_blank">publication</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1909.07750v5" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/mdp-playground" title="code" target="_blank">code</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1613/jair.1.14314" title="Follow DOI:10.1613/jair.1.14314" target="_blank">doi:10.1613/jair.1.14314</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('304','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_conference"><td class="tp_pub_info"><p class="tp_pub_author"> Arango, Sebastian Pineda; Ferreira, Fabio; Kadra, Arlind; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2306.03828" title="arxiv" target="blank">Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How</a> <span class="tp_pub_type conference">Conference</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_303" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('303','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@conference{nokey,<br /> title = {Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How},<br /> author = {Sebastian Pineda Arango and Fabio Ferreira and Arlind Kadra and Frank Hutter and Josif Grabocka},<br /> year = {2023},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_303" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2306.03828" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('303','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Benjamins, Carolin; Eimer, Theresa; Schubert, Frederik; Mohan, Aditya; Döhler, Sebastian; Biedenkapp, André; Rosenhan, Bodo; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=Y42xVBQusn" title="OpenReview" target="blank">Contextualize Me - The Case for Context in Reinforcement Learning</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Transactions on Machine Learning Research, </span><span class="tp_pub_additional_year">2023</span>, <span class="tp_pub_additional_isbn">ISBN: 2835-8856</span>.</p><div class="tp_bibtex" id="tp_bibtex_301" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('301','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{benjamins-tmlr23a,<br /> title = {Contextualize Me - The Case for Context in Reinforcement Learning},<br /> author = {Carolin Benjamins and Theresa Eimer and Frederik Schubert and Aditya Mohan and Sebastian Döhler and André Biedenkapp and Bodo Rosenhan and Frank Hutter and Marius Lindauer},<br /> editor = {Adam M White},<br /> year = {2023},<br /> isbn = {2835-8856},<br /> journal = {Transactions on Machine Learning Research},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_301" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=Y42xVBQusn" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2202.04500" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/CARL" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('301','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_online"><td class="tp_pub_info"><p class="tp_pub_author"> Awad, Noor; Sharma, Ayushi; Müller, Philipp; Thomas, Janek; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2305.04502" title="arXiv " target="blank">MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization</a> <span class="tp_pub_type online">Online</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2023</span><span class="tp_pub_additional_urldate">, visited: 09.05.2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_300" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('300','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@online{Awad-arXiv-2023,<br /> title = {MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization},<br /> author = {Noor Awad and Ayushi Sharma and Philipp Müller and Janek Thomas and Frank Hutter},<br /> year = {2023},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_300" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2305.04502" title="arXiv " target="_blank">arXiv </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2023/05/MO_DEHB_Arxiv23_Appendix-3.pdf" title="Appendix" target="_blank">Appendix</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('300','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Elsken, Thomas; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=paGvsrl4Ntr" title="OpenReview" target="blank">Transfer NAS with Meta-learned Bayesian Surrogates</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">The Eleventh International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2023</span><span class="tp_pub_additional_note">, (<mark>top 5% of accepted papers</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_297" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('297','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala2023transfer,<br /> title = {Transfer NAS with Meta-learned Bayesian Surrogates},<br /> author = {Gresa Shala and Thomas Elsken and Frank Hutter and Josif Grabocka},<br /> year = {2023},<br /> booktitle = {The Eleventh International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_297" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=paGvsrl4Ntr" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('297','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Biedenkapp, André; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=rmoMvptXK7M" title="Openreview" target="blank">Gray-Box Gaussian Processes for Automated Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Eleventh International Conference on Learning Representations (ICLR'23), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_294" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('294','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala-iclr23a,<br /> title = {Gray-Box Gaussian Processes for Automated Reinforcement Learning},<br /> author = {Gresa Shala and André Biedenkapp and Frank Hutter and Josif Grabocka},<br /> year = {2023},<br /> booktitle = {Eleventh International Conference on Learning Representations (ICLR'23)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_294" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=rmoMvptXK7M" title="Openreview" target="_blank">Openreview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/releaunifreiburg/RCGP" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('294','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=cp5PvcI6w8_" title="OpenReview" target="blank">TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">The Eleventh International Conference on Learning Representations (ICLR), </span><span class="tp_pub_additional_year">2023</span><span class="tp_pub_additional_note">, (<mark> top-25% of accepted papers </mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_298" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('298','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{hollmann2023tabpfn,<br /> title = {TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second},<br /> author = {Noah Hollmann and Samuel Müller and Katharina Eggensperger and Frank Hutter},<br /> year = {2023},<br /> booktitle = {The Eleventh International Conference on Learning Representations (ICLR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_298" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=cp5PvcI6w8_" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('298','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Hellsten, Erik; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2304.11005" title="arXiv" target="blank">Self-Correcting Bayesian Optimization through Bayesian Active Learning</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_305" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('305','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{hvarfner2023selfcorrecting,<br /> title = {Self-Correcting Bayesian Optimization through Bayesian Active Learning},<br /> author = {Carl Hvarfner and Erik Hellsten and Frank Hutter and Luigi Nardi},<br /> year = {2023},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_305" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2304.11005" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('305','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Eggensperger, Katharina; Bergman, Edward; Pfisterer, Florian; Bischl, Bernd; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.1007/978-3-031-30047-9_11" title="Mind the Gap: Measuring Generalization Performance Across Multiple Objectives" target="blank">Mind the Gap: Measuring Generalization Performance Across Multiple Objectives</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Crémilleux, Bruno; Hess, Sibylle; Nijssen, Siegfried (Ed.): <span class="tp_pub_additional_booktitle">Advances in Intelligent Data Analysis XXI. IDA 2023., </span><span class="tp_pub_additional_pages">pp. 130-142, </span><span class="tp_pub_additional_publisher">Springer, Cham, </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_293" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('293','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{feurer-ida23a,<br /> title = {Mind the Gap: Measuring Generalization Performance Across Multiple Objectives},<br /> author = {Matthias Feurer and Katharina Eggensperger and Edward Bergman and Florian Pfisterer and Bernd Bischl and Frank Hutter},<br /> editor = {Crémilleux, Bruno and Hess, Sibylle and Nijssen, Siegfried},<br /> doi = {https://doi.org/10.1007/978-3-031-30047-9_11},<br /> year = {2023},<br /> booktitle = {Advances in Intelligent Data Analysis XXI. IDA 2023.},<br /> volume = {13876},<br /> pages = {130-142},<br /> publisher = {Springer, Cham},<br /> series = {Lecture Notes in Computer Science},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_293" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2212.04183" title="arXiv" target="_blank">arXiv</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.1007/978-3-031-30047-9_11" title="Follow DOI:https://doi.org/10.1007/978-3-031-30047-9_11" target="_blank">doi:https://doi.org/10.1007/978-3-031-30047-9_11</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('293','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Weerts, Hilde; Pfisterer, Florian; Feurer, Matthias; Eggensperger, Katharina; Bergman, Edward; Awad, Noor; Vanschoren, Joaquin; Pechenizkiy, Mykola; Bischl, Bernd; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2303.08485" title="arXiv" target="blank">Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2303.08485 [cs.AI], </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_296" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('296','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{weerts-arxiv23a,<br /> title = {Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML},<br /> author = {Hilde Weerts and Florian Pfisterer and Matthias Feurer and Katharina Eggensperger and Edward Bergman and Noor Awad and Joaquin Vanschoren and Mykola Pechenizkiy and Bernd Bischl and Frank Hutter},<br /> year = {2023},<br /> journal = {arXiv:2303.08485 [cs.AI]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_296" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2303.08485" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('296','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_online"><td class="tp_pub_info"><p class="tp_pub_author"> White, Colin; Safari, Mahmoud; Sukthanker, Rhea; Ru, Binxin; Elsken, Thomas; Zela, Arber; Dey, Debadeepta; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2301.08727" title="arxiv" target="blank">Neural Architecture Search: Insights from 1000 Papers</a> <span class="tp_pub_type online">Online</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2023</span><span class="tp_pub_additional_urldate">, visited: 20.01.2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_295" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('295','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@online{white2023neural,<br /> title = {Neural Architecture Search: Insights from 1000 Papers},<br /> author = {Colin White and Mahmoud Safari and Rhea Sukthanker and Binxin Ru and Thomas Elsken and Arber Zela and Debadeepta Dey and Frank Hutter},<br /> year = {2023},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_295" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2301.08727" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('295','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Schrodi, Simon; Stoll, Danny; Ru, Binxin; Sukthanker, Rhea; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2211.01842" title="arXiv" target="blank">Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_306" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('306','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{schrodi2023construction,<br /> title = {Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars},<br /> author = {Simon Schrodi and Danny Stoll and Binxin Ru and Rhea Sukthanker and Thomas Brox and Frank Hutter},<br /> year = {2023},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_306" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2211.01842" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('306','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hollmann, Noah; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=9WSxQZ9mG7" title="https://openreview.net/forum?id=9WSxQZ9mG7" target="blank">LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), </span><span class="tp_pub_additional_year">2023</span>.</p><div class="tp_bibtex" id="tp_bibtex_311" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('311','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{<LineBreak>anonymous2023llms,<br /> title = {LLMs for Semi-Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering},<br /> author = {Noah Hollmann and Samuel Müller and Frank Hutter},<br /> year = {2023},<br /> booktitle = {Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_311" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=9WSxQZ9mG7" title="https://openreview.net/forum?id=9WSxQZ9mG7" target="_blank">https://openreview.net/forum?id=9WSxQZ9mG7</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('311','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2022">2022</h3> </td> </tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Adriaensen, Steven; Biedenkapp, André; Shala, Gresa; Awad, Noor; Eimer, Theresa; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1613/jair.1.13922 " title="Automated Dynamic Algorithm Configuration" target="blank">Automated Dynamic Algorithm Configuration</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research (JAIR), </span><span class="tp_pub_additional_volume">vol. 75, </span><span class="tp_pub_additional_pages">pp. 1633-1699, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_259" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('259','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{adriaens-arxiv22a,<br /> title = {Automated Dynamic Algorithm Configuration},<br /> author = {Steven Adriaensen and André Biedenkapp and Gresa Shala and Noor Awad and Theresa Eimer and Marius Lindauer and Frank Hutter},<br /> doi = {10.1613/jair.1.13922 },<br /> year = {2022},<br /> journal = {Journal of Artificial Intelligence Research (JAIR)},<br /> volume = {75},<br /> pages = {1633-1699},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_259" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.jair.org/index.php/jair/article/view/13922" title="published" target="_blank">published</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2205.13881" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/2022_JAIR_DAC_experiments" title="code" target="_blank">code</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1613/jair.1.13922 " title="Follow DOI:10.1613/jair.1.13922 " target="_blank">doi:10.1613/jair.1.13922 </a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('259','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg; Runge, Frederic; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=RF74aWLrvBp" title="OpenReview" target="blank">Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): <span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems (NeurIPS 2022), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_276" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('276','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{franke2022probabilistic,<br /> title = {Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design},<br /> author = {Jörg Franke and Frederic Runge and Frank Hutter},<br /> editor = {Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},<br /> year = {2022},<br /> booktitle = {Advances in Neural Information Processing Systems (NeurIPS 2022)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_276" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=RF74aWLrvBp" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('276','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=4R5x8no2Ts-" title="OpenReview" target="blank">Joint Entropy Search For Maximally-Informed Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun (Ed.): <span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems (NeurIPS 2022), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_275" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('275','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{hvarfner2022joint,<br /> title = {Joint Entropy Search For Maximally-Informed Bayesian Optimization},<br /> author = {Carl Hvarfner and Frank Hutter and Luigi Nardi},<br /> editor = {Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},<br /> year = {2022},<br /> booktitle = {Advances in Neural Information Processing Systems (NeurIPS 2022)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_275" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=4R5x8no2Ts-" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('275','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Bansal, Archit; Stoll, Danny; Janowski, Maciej; Zela, Arber; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=_HLcjaVlqJ" title="OpenReview" target="blank">JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-sixth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span><span class="tp_pub_additional_note">, (<mark>Featured Paper - top 7.5% of accepted papers</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_267" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('267','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{bansal-neurips22a,<br /> title = {JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search},<br /> author = {Archit Bansal and Danny Stoll and Maciej Janowski and Arber Zela and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Thirty-sixth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_267" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=_HLcjaVlqJ" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('267','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Arango, Sebastian Pineda; Biedenkapp, André; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=RyAl60VhTcG" title="Openreview" target="blank">AutoRL-Bench 1.0</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Meta-Learning (MetaLearn@NeurIPS'22), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_271" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('271','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala-metalearn22a,<br /> title = {AutoRL-Bench 1.0},<br /> author = {Gresa Shala and Sebastian Pineda Arango and André Biedenkapp and Frank Hutter and Josif Grabocka},<br /> year = {2022},<br /> booktitle = {Workshop on Meta-Learning (MetaLearn@NeurIPS'22)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_271" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=RyAl60VhTcG" title="Openreview" target="_blank">Openreview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('271','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Biedenkapp, André; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=oJp7uTL7ox-" title="Openreview" target="blank">Gray-Box Gaussian Processes for Automated Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Meta-Learning (MetaLearn@NeurIPS'22), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_272" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('272','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala-metalearn22b,<br /> title = {Gray-Box Gaussian Processes for Automated Reinforcement Learning},<br /> author = {Gresa Shala and André Biedenkapp and Frank Hutter and Josif Grabocka},<br /> year = {2022},<br /> booktitle = {Workshop on Meta-Learning (MetaLearn@NeurIPS'22)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_272" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=oJp7uTL7ox-" title="Openreview" target="_blank">Openreview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('272','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Krishnakumar, Arjun; White, Colin; Zela, Arber; Tu, Renbo; Safari, Mahmoud; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=yWhuIjIjH8k" title="OpenReview" target="blank">NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-sixth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_277" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('277','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{krishnakumar2022nasbenchsuitezero,<br /> title = {NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies},<br /> author = {Arjun Krishnakumar and Colin White and Arber Zela and Renbo Tu and Mahmoud Safari and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Thirty-sixth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_277" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=yWhuIjIjH8k" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('277','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Roberts, Nicholas; Guo, Samuel; Xu, Cong; Talwalkar, Ameet; Lander, David; Tao, Lvfang; Cai, Linhang; Niu, Shuaicheng; Heng, Jianyu; Qin, Hongyang; Deng, Minwen; Hog, Johannes; Pfefferle, Alexander; Shivakumar, Sushil Ammanaghatta; Krishnakumar, Arjun; Wang, Yubo; Sukthanker, Rhea; Hutter, Frank; Hasanaj, Euxhen; Le, Tien-Dung; Khodak, Mikhail; Nevmyvaka, Yuriy; Rasul, Kashif; Sala, Frederic; Schneider, Anderson; Shen, Junhong; Sparks, Evan</p><p class="tp_pub_title"><a class="tp_title_link" href="https://proceedings.mlr.press/v220/roberts23a.html" title="https://proceedings.mlr.press/v220/roberts23a.html" target="blank">AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Ciccone, Marco; Stolovitzky, Gustavo; Albrecht, Jacob (Ed.): <span class="tp_pub_additional_booktitle">Proceedings of the NeurIPS 2022 Competitions Track, </span><span class="tp_pub_additional_pages">pp. 151–170, </span><span class="tp_pub_additional_publisher">PMLR, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_401" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('401','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{pmlr-v220-roberts23a,<br /> title = {AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale},<br /> author = {Nicholas Roberts and Samuel Guo and Cong Xu and Ameet Talwalkar and David Lander and Lvfang Tao and Linhang Cai and Shuaicheng Niu and Jianyu Heng and Hongyang Qin and Minwen Deng and Johannes Hog and Alexander Pfefferle and Sushil Ammanaghatta Shivakumar and Arjun Krishnakumar and Yubo Wang and Rhea Sukthanker and Frank Hutter and Euxhen Hasanaj and Tien-Dung Le and Mikhail Khodak and Yuriy Nevmyvaka and Kashif Rasul and Frederic Sala and Anderson Schneider and Junhong Shen and Evan Sparks},<br /> editor = {Marco Ciccone and Gustavo Stolovitzky and Jacob Albrecht},<br /> year = {2022},<br /> booktitle = {Proceedings of the NeurIPS 2022 Competitions Track},<br /> volume = {220},<br /> pages = {151--170},<br /> publisher = {PMLR},<br /> series = {Proceedings of Machine Learning Research},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_401" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://proceedings.mlr.press/v220/roberts23a.html" title="https://proceedings.mlr.press/v220/roberts23a.html" target="_blank">https://proceedings.mlr.press/v220/roberts23a.html</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('401','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Eggensperger, Katharina; Falkner, Stefan; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.jmlr.org/papers/v23/21-0992.html" title="published" target="blank">Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Machine Learning Research, </span><span class="tp_pub_additional_volume">vol. 23, </span><span class="tp_pub_additional_number">no. 261, </span><span class="tp_pub_additional_pages">pp. 1-61, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_46" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('46','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{feurer-jmlr22a,<br /> title = {Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning},<br /> author = {Matthias Feurer and Katharina Eggensperger and Stefan Falkner and Marius Lindauer and Frank Hutter},<br /> editor = {Marc Schoenauer},<br /> year = {2022},<br /> journal = {Journal of Machine Learning Research},<br /> volume = {23},<br /> number = {261},<br /> pages = {1-61},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_46" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.jmlr.org/papers/v23/21-0992.html" title="published" target="_blank">published</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-0992.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/ASKL2.0_experiments" title="code" target="_blank">code</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2007.04074" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('46','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2206.04771" title="arxiv" target="blank">Joint Entropy Search For Maximally-Informed Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_264" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('264','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{hvarfner-realml22a,<br /> title = {Joint Entropy Search For Maximally-Informed Bayesian Optimization},<br /> author = {Carl Hvarfner and Frank Hutter and Luigi Nardi},<br /> year = {2022},<br /> booktitle = {Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_264" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2206.04771" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://realworldml.github.io/files/cr/paper20.pdf" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('264','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Sass, René; Bergman, Eddie; Biedenkapp, André; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2206.03493" title="arxiv" target="blank">DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_262" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('262','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{sass-arxiv22,<br /> title = {DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning},<br /> author = {René Sass and Eddie Bergman and André Biedenkapp and Frank Hutter and Marius Lindauer},<br /> year = {2022},<br /> booktitle = {Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML@ICML'22)},<br /> journal = {arXiv:2206.03493 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_262" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2206.03493" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/deepcave" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('262','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Dang, Nguyen; Krejca, Martin S.; Hutter, Frank; Doerr, Carola</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2202.03259" title="arxiv" target="blank">Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22), </span><span class="tp_pub_additional_year">2022</span><span class="tp_pub_additional_note">, (<mark>Won the best paper award in the <a href="https://gecco-2022.sigevo.org/Best-Paper-Nominations">GECH track</a></mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_251" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('251','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-gecco22a,<br /> title = {Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration},<br /> author = {André Biedenkapp and Nguyen Dang and Martin S. Krejca and Frank Hutter and Carola Doerr},<br /> year = {2022},<br /> booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'22)},<br /> journal = {arXiv:2202.03259},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_251" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2202.03259" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/ndangtt/LeadingOnesDAC" title="code" target="_blank">code</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://andrebiedenkapp.github.io/blog/2022/gecco/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('251','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Speck, David; Sievers, Silvan; Hutter, Frank; Lindauer, Marius; Seipp, Jendrik</p><p class="tp_pub_title"><a class="tp_title_link" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2022/06/22-PRL-DAC4AIPlanning.pdf" title="pdf" target="blank">Learning Domain-Independent Policies for Open List Selection</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL @ ICAPS'22), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_260" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('260','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-prl22a,<br /> title = {Learning Domain-Independent Policies for Open List Selection},<br /> author = {André Biedenkapp and David Speck and Silvan Sievers and Frank Hutter and Marius Lindauer and Jendrik Seipp},<br /> year = {2022},<br /> booktitle = {Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL @ ICAPS'22)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_260" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2022/06/22-PRL-DAC4AIPlanning.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://youtu.be/RgyYaJIr4p8" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('260','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Wagner, Diane; Ferreira, Fabio; Stoll, Danny; Schirrmeister, Robin Tibor; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2207.07875" title="arxiv" target="blank">On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">ICML Pre-training Workshop, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_265" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('265','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{ferreira-icml22b,<br /> title = {On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning},<br /> author = {Diane Wagner and Fabio Ferreira and Danny Stoll and Robin Tibor Schirrmeister and Samuel Müller and Frank Hutter},<br /> year = {2022},<br /> booktitle = {ICML Pre-training Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_265" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2207.07875" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('265','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Öztürk*, Ekrem; Ferreira*, Fabio; Jomaa*, Hadi S.; Schmidt-Thieme, Lars; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2206.08476" title="arxiv" target="blank">Zero-shot AutoML with Pretrained Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Machine Learning (ICML), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_261" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('261','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{ferreira-icml22a,<br /> title = {Zero-shot AutoML with Pretrained Models},<br /> author = {Ekrem Öztürk* and Fabio Ferreira* and Hadi S. Jomaa* and Lars Schmidt-Thieme and Josif Grabocka and Frank Hutter},<br /> year = {2022},<br /> booktitle = {International Conference on Machine Learning (ICML)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_261" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2206.08476" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/zero-shot-automl-with-pretrained-models" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('261','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Parker-Holder, Jack; Rajan, Raghu; Song, Xingyou; Biedenkapp, André; Miao, Yingjie; Eimer, Theresa; Zhang, Baohe; Nguyen, Vu; Calandra, Roberto; Faust, Aleksandra; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://jair.org/index.php/jair/article/view/13596" title="publication" target="blank">Automated Reinforcement Learning (AutoRL): A Survey and Open Problems</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research (JAIR), </span><span class="tp_pub_additional_volume">vol. 74, </span><span class="tp_pub_additional_pages">pp. 517-568, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_246" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('246','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{parker-holder-jair22a,<br /> title = {Automated Reinforcement Learning (AutoRL): A Survey and Open Problems},<br /> author = {Jack Parker-Holder and Raghu Rajan and Xingyou Song and André Biedenkapp and Yingjie Miao and Theresa Eimer and Baohe Zhang and Vu Nguyen and Roberto Calandra and Aleksandra Faust and Frank Hutter and Marius Lindauer},<br /> year = {2022},<br /> journal = {Journal of Artificial Intelligence Research (JAIR)},<br /> volume = {74},<br /> pages = {517-568},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_246" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jair.org/index.php/jair/article/view/13596" title="publication" target="_blank">publication</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2201.03916" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('246','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Mehta*, Yash; White*, Colin; Zela, Arber; Krishnakumar, Arjun; Zabergja, Guri; Moradian, Shakiba; Safari, Mahmoud; Yu, Kaicheng; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/pdf/2201.13396.pdf" title="https://arxiv.org/pdf/2201.13396.pdf" target="blank">NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR) 2022, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_254" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('254','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mehta-iclr22,<br /> title = {NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy},<br /> author = {Yash Mehta* and Colin White* and Arber Zela and Arjun Krishnakumar and Guri Zabergja and Shakiba Moradian and Mahmoud Safari and Kaicheng Yu and Frank Hutter},<br /> year = {2022},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2022},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_254" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://arxiv.org/pdf/2201.13396.pdf" title="https://arxiv.org/pdf/2201.13396.pdf" target="_blank">https://arxiv.org/pdf/2201.13396.pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('254','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Samuel; Hollmann, Noah; Arango, Sebastian Pineda; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2112.10510" title="Arxiv" target="blank">Transformers Can Do Bayesian Inference</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">10th International Conference on Learning Representations, ICLR 2022, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_248" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('248','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{nokey,<br /> title = {Transformers Can Do Bayesian Inference},<br /> author = {Samuel Müller and Noah Hollmann and Sebastian Pineda Arango and Josif Grabocka and Frank Hutter},<br /> year = {2022},<br /> booktitle = {10th International Conference on Learning Representations, ICLR 2022},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_248" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2112.10510" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('248','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zela, Arber; Siems, Julien; Zimmer, Lucas; Lukasik, Jovita; Keuper, Margret; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/pdf?id=OnpFa95RVqs" title="https://openreview.net/pdf?id=OnpFa95RVqs" target="blank">Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR), </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_255" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('255','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{zela-iclr21,<br /> title = {Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks},<br /> author = {Arber Zela and Julien Siems and Lucas Zimmer and Jovita Lukasik and Margret Keuper and Frank Hutter},<br /> year = {2022},<br /> booktitle = {International Conference on Learning Representations (ICLR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_255" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/pdf?id=OnpFa95RVqs" title="https://openreview.net/pdf?id=OnpFa95RVqs" target="_blank">https://openreview.net/pdf?id=OnpFa95RVqs</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('255','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hvarfner, Carl; Stoll, Danny; Souza, Artur; Lindauer, Marius; Hutter, Frank; Nardi, Luigi</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=MMAeCXIa89" title="publication" target="blank">πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">10th International Conference on Learning Representations, ICLR 2022, </span><span class="tp_pub_additional_publisher">OpenReview.net, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_249" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('249','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Hvarfner0000,<br /> title = {πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization},<br /> author = {Carl Hvarfner and Danny Stoll and Artur Souza and Marius Lindauer and Frank Hutter and Luigi Nardi},<br /> year = {2022},<br /> booktitle = {10th International Conference on Learning Representations, ICLR 2022},<br /> publisher = {OpenReview.net},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_249" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=MMAeCXIa89" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('249','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Benjamins, Carolin; Eimer, Theresa; Schubert, Frederik; Mohan, Aditya; Biedenkapp, André; Rosenhan, Bodo; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2202.04500" title="arxiv" target="blank">Contextualize Me – The Case for Context in Reinforcement Learning</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2202.04500, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_252" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('252','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{benjamins-arxiv22a,<br /> title = {Contextualize Me – The Case for Context in Reinforcement Learning},<br /> author = {Carolin Benjamins and Theresa Eimer and Frederik Schubert and Aditya Mohan and André Biedenkapp and Bodo Rosenhan and Frank Hutter and Marius Lindauer},<br /> year = {2022},<br /> journal = {arXiv:2202.04500},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_252" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2202.04500" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/CARL/tree/icml_2022" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('252','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Ferreira, Fabio; Nierhoff, Thomas; Sälinger, Andreas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="http://arxiv.org/abs/2202.02790" title="arxiv" target="blank">Learning Synthetic Environments and Reward Networks for Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">10th International Conference on Learning Representations (ICLR), OpenReview.net, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_250" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('250','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{,<br /> title = {Learning Synthetic Environments and Reward Networks for Reinforcement Learning},<br /> author = {Fabio Ferreira and Thomas Nierhoff and Andreas Sälinger and Frank Hutter},<br /> year = {2022},<br /> booktitle = {10th International Conference on Learning Representations (ICLR), OpenReview.net},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_250" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/2202.02790" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=C1_esHN6AVn" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/learning_environments" title="Code" target="_blank">Code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('250','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, Marius; Eggensperger, Katharina; Feurer, Matthias; Biedenkapp, André; Deng, Difan; Benjamins, Carolin; Ruhkopf, Tim; Sass, René; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2109.09831" title="arXiv" target="blank"> SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Machine Learning Research (JMLR) -- MLOSS, </span><span class="tp_pub_additional_volume">vol. 23, </span><span class="tp_pub_additional_number">no. 54, </span><span class="tp_pub_additional_pages">pp. 1-9, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_236" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('236','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lindauer-jmlr22a,<br /> title = { SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization},<br /> author = {Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Difan Deng and Carolin Benjamins and Tim Ruhkopf and René Sass and Frank Hutter},<br /> year = {2022},<br /> journal = {Journal of Machine Learning Research (JMLR) -- MLOSS},<br /> volume = {23},<br /> number = {54},<br /> pages = {1-9},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_236" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2109.09831" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/SMAC3" title="code" target="_blank">code</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jmlr.org/papers/v23/21-0888.html" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('236','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Letham, Benjamin; Hutter, Frank; Bakshy, Eytan</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1802.02219" title="arXiv" target="blank">Practical Transfer Learning for Bayesian Optimization</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:1802:02219v3 [stat.ML], </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_247" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('247','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{feurer-arxiv22a,<br /> title = {Practical Transfer Learning for Bayesian Optimization},<br /> author = {Matthias Feurer and Benjamin Letham and Frank Hutter and Eytan Bakshy },<br /> year = {2022},<br /> journal = {arXiv:1802:02219v3 [stat.ML]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_247" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1802.02219" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('247','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_workshop"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Samuel; Arango, Sebastian Pineda; Feurer, Matthias; Grabocka, Josif; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=9xCudkMSkC" title="OpenReview" target="blank">Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only</a> <span class="tp_pub_type workshop">Workshop</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_273" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('273','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@workshop{müller2022bayesian,<br /> title = {Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only},<br /> author = {Samuel Müller and Sebastian Pineda Arango and Matthias Feurer and Josif Grabocka and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_273" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=9xCudkMSkC" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('273','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://gp-seminar-series.github.io/neurips-2022/" title="Workshop website" target="blank">c-TPE: Generalizing Tree-structured Parzen Estimator with Inequality Constraints for Continuous and Categorical Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_291" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('291','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{watanabe2022cTPE,<br /> title = {c-TPE: Generalizing Tree-structured Parzen Estimator with Inequality Constraints for Continuous and Categorical Hyperparameter Optimization},<br /> author = {Shuhei Watanabe and Frank Hutter},<br /> year = {2022},<br /> booktitle = {NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_291" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://gp-seminar-series.github.io/neurips-2022/" title="Workshop website" target="_blank">Workshop website</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('291','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Adriaensen, Steven; Rakotoarison, Herilalaina; Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=VQpqxucNX63" title="OpenReview" target="blank">Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_280" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('280','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{adriaensen2022efficientb,<br /> title = {Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks},<br /> author = {Steven Adriaensen and Herilalaina Rakotoarison and Samuel Müller and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_280" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=VQpqxucNX63" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('280','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Sukthanker, Rhea Sanjay; Krishnakumar, Arjun; Patil, Sharat; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=dm8WcWiuvd" title="OpenReview" target="blank">GraViT-E: Gradient-based Vision Transformer Search with Entangled Weights</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_283" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('283','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{sukthanker2022gravite,<br /> title = {GraViT-E: Gradient-based Vision Transformer Search with Entangled Weights},<br /> author = {Rhea Sanjay Sukthanker and Arjun Krishnakumar and Sharat Patil and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_283" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=dm8WcWiuvd" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('283','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Watanabe, Shuhei; Awad, Noor; Onishi, Masaki; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=vBcKu0UL3A9" title="OpenReview" target="blank">Multi-objective Tree-structured Parzen Estimator Meets Meta-learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_282" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('282','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{watanabe2022multiobjective,<br /> title = {Multi-objective Tree-structured Parzen Estimator Meets Meta-learning},<br /> author = {Shuhei Watanabe and Noor Awad and Masaki Onishi and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_282" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=vBcKu0UL3A9" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('282','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Dooley, Samuel; Sukthanker, Rhea Sanjay; Dickerson, John P; White, Colin; Hutter, Frank; Goldblum, Micah</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=NpuYNxmIHrc" title="OpenReview" target="blank">On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_286" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('286','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{dooley2022on,<br /> title = {On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition},<br /> author = {Samuel Dooley and Rhea Sanjay Sukthanker and John P Dickerson and Colin White and Frank Hutter and Micah Goldblum},<br /> year = {2022},<br /> booktitle = {Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_286" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=NpuYNxmIHrc" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('286','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Dooley, Samuel; Sukthanker, Rhea Sanjay; Dickerson, John P; White, Colin; Hutter, Frank; Goldblum, Micah</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=geTXQoibWcI" title="OpenReview" target="blank">On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_285" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('285','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{dooley2022on,<br /> title = {On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition},<br /> author = {Samuel Dooley and Rhea Sanjay Sukthanker and John P Dickerson and Colin White and Frank Hutter and Micah Goldblum},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_285" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=geTXQoibWcI" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('285','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Mallik, Neeratyoy; Hvarfner, Carl; Stoll, Danny; Janowski, Maciej; Bergman, Eddie; Lindauer, Marius; Nardi, Luigi; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=ds21dwfBBH" title="OpenReview" target="blank">PriorBand: HyperBand + Human Expert Knowledge</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_284" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('284','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mallik-neurips22a,<br /> title = {PriorBand: HyperBand + Human Expert Knowledge},<br /> author = {Neeratyoy Mallik and Carl Hvarfner and Danny Stoll and Maciej Janowski and Eddie Bergman and Marius Lindauer and Luigi Nardi and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_284" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=ds21dwfBBH" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('284','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hollmann, Noah; Müller, Samuel; Eggensperger, Katharina; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2207.01848" title="Arxiv" target="blank">TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2022 First Table Representation Workshop, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_274" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('274','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{hollmann2022tabpfn,<br /> title = {TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second},<br /> author = {Noah Hollmann and Samuel Müller and Katharina Eggensperger and Frank Hutter},<br /> year = {2022},<br /> booktitle = {NeurIPS 2022 First Table Representation Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_274" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2207.01848" title="Arxiv" target="_blank">Arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('274','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Elsken, Thomas; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=fqKBtyLqikY" title="OpenReview" target="blank">Transfer NAS with Meta-learned Bayesian Surrogates</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_290" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('290','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala2022transfer,<br /> title = {Transfer NAS with Meta-learned Bayesian Surrogates},<br /> author = {Gresa Shala and Thomas Elsken and Frank Hutter and Josif Grabocka},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_290" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=fqKBtyLqikY" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('290','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Schrodi, Simon; Stoll, Danny; Ru, Binxin; Sukthanker, Rhea Sanjay; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=Ok58hMNXIQ" title="OpenReview" target="blank">Towards Discovering Neural Architectures from Scratch</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2022</span>.</p><div class="tp_bibtex" id="tp_bibtex_278" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('278','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{schrodi2022towards,<br /> title = {Towards Discovering Neural Architectures from Scratch},<br /> author = {Simon Schrodi and Danny Stoll and Binxin Ru and Rhea Sanjay Sukthanker and Thomas Brox and Frank Hutter},<br /> year = {2022},<br /> booktitle = {Sixth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_278" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=Ok58hMNXIQ" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('278','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2021">2021</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Gijsbers, Pieter; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin</p><p class="tp_pub_title"><a class="tp_title_link" href="https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c7e1249ffc03eb9ded908c236bd1996d-Abstract-round2.html" title="NeurIPS.cc" target="blank">OpenML Benchmarking Suites </a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_241" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('241','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{bischl-neurips21a,<br /> title = {OpenML Benchmarking Suites },<br /> author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Pieter Gijsbers and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},<br /> year = {2021},<br /> booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_241" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c7e1249ffc03eb9ded908c236bd1996d-Abstract-round2.html" title="NeurIPS.cc" target="_blank">NeurIPS.cc</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2021/11/OCrD8ycKjG.supplemental.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('241','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Benjamins, Carolin; Eimer, Theresa; Schubert, Frederik; Biedenkapp, André; Rosenhan, Bodo; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2110.02102" title="arxiv" target="blank">CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Ecological Theory of Reinforcement Learning (EcoRL@NeurIPS'21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_240" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('240','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{benjamins-arxiv21a,<br /> title = {CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning},<br /> author = {Carolin Benjamins and Theresa Eimer and Frederik Schubert and André Biedenkapp and Bodo Rosenhan and Frank Hutter and Marius Lindauer},<br /> year = {2021},<br /> booktitle = {Workshop on Ecological Theory of Reinforcement Learning (EcoRL@NeurIPS'21)},<br /> journal = {arXiv:2110.02102},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_240" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2110.02102" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/CARL" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('240','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Müller, Philipp; Mallik, Neeratyoy; Feurer, Matthias; Sass, René; Klein, Aaron; Awad, Noor; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2109.06716v2" title="arxiv" target="blank">HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Vanschoren, J.; Yeung, S. (Ed.): <span class="tp_pub_additional_booktitle">Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_239" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('239','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eggensperger-neuripsdbt21,<br /> title = {HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO},<br /> author = {Katharina Eggensperger and Philipp Müller and Neeratyoy Mallik and Matthias Feurer and René Sass and Aaron Klein and Noor Awad and Marius Lindauer and Frank Hutter},<br /> editor = {J. Vanschoren and S. Yeung},<br /> year = {2021},<br /> booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},<br /> journal = {arXiv:2109.06716},<br /> volume = {1},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_239" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2109.06716v2" title="arxiv" target="_blank">arxiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/HPOBench" title="code" target="_blank">code</a></li><li><i class="fas fa-file-image"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2021/12/2020_HPOBench.png" title="poster" target="_blank">poster</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2021/12/HPOBench_slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://www.youtube.com/watch?v=Fe5k69mESWQ" title="video" target="_blank">video</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/93db85ed909c13838ff95ccfa94cebd9-Abstract-round2.html" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('239','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eimer, Theresa; Biedenkapp, André; Reimer, Maximilian; Adriaensen, Steven; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-IJCAI-DACBench.pdf" title="pdf " target="blank">DACBench: A Benchmark Library for Dynamic Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI'21), </span><span class="tp_pub_additional_publisher">ijcai.org, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_33" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('33','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eimer-ijcai21,<br /> title = {DACBench: A Benchmark Library for Dynamic Algorithm Configuration},<br /> author = {Theresa Eimer and André Biedenkapp and Maximilian Reimer and Steven Adriaensen and Frank Hutter and Marius Lindauer},<br /> year = {2021},<br /> booktitle = {Proceedings of the Thirtieth International Joint Conference on <br /> Artificial Intelligence (IJCAI'21)},<br /> publisher = {ijcai.org},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_33" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-IJCAI-DACBench.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.ijcai.org/proceedings/2021/230" title="publication" target="_blank">publication</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/DACBench" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2105.08541" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/dacbench-benchmarking-dynamic-algorithm-configuration/" title="blog" target="_blank">blog</a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://youtu.be/-G-hLmBI4WM" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('33','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Speck, David; Biedenkapp, André; Hutter, Frank; Mattmüller, Robert; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-ICAPS-DAC-PLAN.pdf" title="pdf " target="blank">Learning Heuristic Selection with Dynamic Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS'21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_187" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('187','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{speck-icaps21,<br /> title = {Learning Heuristic Selection with Dynamic Algorithm Configuration},<br /> author = {David Speck and André Biedenkapp and Frank Hutter and Robert Mattmüller and Marius Lindauer},<br /> year = {2021},<br /> booktitle = {Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS'21)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_187" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ICAPS-DAC-PLAN.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://ojs.aaai.org/index.php/ICAPS/article/view/16008" title="publication " target="_blank">publication </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/speckdavid/rl-plan" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.08246" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://icaps21.icaps-conference.org/exhibition/index.html?channel=152" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('187','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Awad, Noor; Mallik, Neeratyoy; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-IJCAI-DEHB.pdf" title="pdf " target="blank">DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI'21), </span><span class="tp_pub_additional_publisher">ijcai.org, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_4" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('4','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{awad-ijcai21,<br /> title = {DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization},<br /> author = {Noor Awad and Neeratyoy Mallik and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Proceedings of the Thirtieth International Joint Conference on <br /> Artificial Intelligence (IJCAI'21)},<br /> publisher = {ijcai.org},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_4" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-IJCAI-DEHB.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-IJCAI-DEHB-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/DEHB" title="code" target="_blank">code</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://ijcai-21.org/videos-slides/?video=4722" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('4','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Narayanan, Ashwin Raaghav; Zela, Arber; Saikia, Tonmoy; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2021/08/2107.04369.pdf" title="pdf" target="blank">Multi-headed Neural Ensemble Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Uncertainty and Robustness in Deep Learning (UDL@ICML`21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_235" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('235','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Narayanan2021b,<br /> title = {Multi-headed Neural Ensemble Search},<br /> author = {Ashwin Raaghav Narayanan and Arber Zela and Tonmoy Saikia and Thomas Brox and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Workshop on Uncertainty and Robustness in Deep Learning (UDL@ICML`21)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_235" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2021/08/2107.04369.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://www.gatsby.ucl.ac.uk/~balaji/udl2021/accepted-papers/UDL2021-paper-065.pdf" title="publication" target="_blank">publication</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2107.04369" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('235','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eimer, Theresa; Biedenkapp, André; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-ICML-SPaCE-poster.pdf" title="poster " target="blank">Self-Paced Context Evaluations for Contextual Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 38th International Conference on Machine Learning (ICML 2021), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_32" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('32','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eimer-icml21,<br /> title = {Self-Paced Context Evaluations for Contextual Reinforcement Learning},<br /> author = {Theresa Eimer and André Biedenkapp and Frank Hutter and Marius Lindauer},<br /> year = {2021},<br /> booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML 2021)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_32" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ICML-SPaCE-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://proceedings.mlr.press/v139/eimer21a.html" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/SPaCE" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2106.05110" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38959253/selfpaced-context-evaluation-for-contextual-reinforcement-learning" title="video" target="_blank">video</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/self-paced-context-evaluation-for-contextual-reinforcement-learning/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('32','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Izquierdo, Sergio; Guerrero-Viu, Julia; Hauns, Sven; Miotto, Guilherme; Schrodi, Simon; Biedenkapp, André; Elsken, Thomas; Deng, Difan; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-ARXIV-BBMoNASHPO-poster.pdf" title="poster " target="blank">Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Automated Machine Learning (AutoML@ICML'21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_227" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('227','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{viu-automlicml21a,<br /> title = {Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization},<br /> author = {Sergio Izquierdo and Julia Guerrero-Viu and Sven Hauns and Guilherme Miotto and Simon Schrodi and André Biedenkapp and Thomas Elsken and Difan Deng and Marius Lindauer and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Workshop on Automated Machine Learning (AutoML@ICML'21)},<br /> journal = {Workshop on Automated Machine Learning (AutoML@ICML'21)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_227" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ARXIV-BBMoNASHPO-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/multi-obj-baselines" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2105.01015" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38962449/bag-of-baselines-for-multiobjective-joint-neural-architecture-search-and-hyperparameter-optimization" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('227','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Rajan, Raghu; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-ICML-TempoRL.pdf" title="pdf " target="blank">TempoRL: Learning When to Act</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 38th International Conference on Machine Learning (ICML 2021), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_12" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('12','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-icml21,<br /> title = {TempoRL: Learning When to Act},<br /> author = {André Biedenkapp and Raghu Rajan and Frank Hutter and Marius Lindauer},<br /> year = {2021},<br /> booktitle = {Proceedings of the 38th International Conference on Machine Learning (ICML 2021)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_12" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ICML-TempoRL.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ICML-TempoRL-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-ICML-TempoRL-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://proceedings.mlr.press/v139/biedenkapp21a.html" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/TempoRL" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/2106.05262" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38959338/temporl-learning-when-to-act" title="video" target="_blank">video</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://andrebiedenkapp.github.io/blog/2022/temporl" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('12','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Rajan, Raghu; Diaz, Jessica Lizeth Borja; Guttikonda, Suresh; Ferreira, Fabio; Biedenkapp, André; von Hartz, Jan Ole; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1909.07750v4" title="arXiv" target="blank">MDP Playground: A Design and Debug Testbed for Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">arXiv:1909.07750, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_159" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('159','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{rajan-arxiv21,<br /> title = {MDP Playground: A Design and Debug Testbed for Reinforcement Learning},<br /> author = {Raghu Rajan and Jessica Lizeth Borja Diaz and Suresh Guttikonda and Fabio Ferreira and André Biedenkapp and Jan Ole von Hartz and Frank Hutter},<br /> year = {2021},<br /> booktitle = {arXiv:1909.07750},<br /> journal = {arXiv:1909.07750v4 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_159" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1909.07750v4" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/mdp-playground" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('159','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author">Colin White Shen Yan, Yash Savani; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2111.03602" title="arxiv" target="blank">NAS-Bench-x11 and the Power of Learning Curves</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_230" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('230','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{yan2021nas,<br /> title = {NAS-Bench-x11 and the Power of Learning Curves},<br /> author = {Shen Yan, Colin White, Yash Savani and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21)},<br /> journal = {CVPR},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_230" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2111.03602" title="arxiv" target="_blank">arxiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('230','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Staffler, Benedikt; Zela, Arber; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2107.03719" title=" arXiv" target="blank">Bag of Tricks for Neural Architecture Search</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_229" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('229','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{elsken2021bag,<br /> title = {Bag of Tricks for Neural Architecture Search},<br /> author = {Thomas Elsken and Benedikt Staffler and Arber Zela and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2021},<br /> journal = {Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_229" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2107.03719" title=" arXiv" target="_blank"> arXiv</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://cvpr21-nas.com/resources/upload/0894f613d1c1/1624351778316/cvpr_nas_ws_bag_of_tricks_crc.pdf" title=" pdf" target="_blank"> pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('229','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Chatzimichailidis, Avraam; Zela, Arber; Shalini, Shalini; Labus, Peter; Keuper, Janis; Hutter, Frank; Yang, Yang</p><p class="tp_pub_title"><a class="tp_title_link" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2022/03/Group_Sparsity.pdf" title="pdf" target="blank">Group Sparsity: A Unified Framework for Network Pruning and Neural Architecture Search</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_232" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('232','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{chatzimichailidisgroup,<br /> title = {Group Sparsity: A Unified Framework for Network Pruning and Neural Architecture Search},<br /> author = {Avraam Chatzimichailidis and Arber Zela and Shalini Shalini and Peter Labus and Janis Keuper and Frank Hutter and Yang Yang},<br /> year = {2021},<br /> journal = {Proceedings of the CVPR 2021 Workshop on Neural Architecture Search (CVPR-NAS '21)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_232" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ml.informatik.uni-freiburg.de/wp-content/uploads/2022/03/Group_Sparsity.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('232','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zaidi, Sheheryar; Zela, Arber; Elsken, Thomas; Holmes, Christopher C.; Hutter, Frank; Teh, Yee Whye</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=HiYDAwAGWud" title="OpenReview" target="blank">Neural Ensemble Search for Uncertainty Estimation and Dataset Shift</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-Fifth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_244" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('244','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{zaidi2021neural,<br /> title = {Neural Ensemble Search for Uncertainty Estimation and Dataset Shift},<br /> author = {Sheheryar Zaidi and Arber Zela and Thomas Elsken and Christopher C. Holmes and Frank Hutter and Yee Whye Teh},<br /> year = {2021},<br /> booktitle = {Thirty-Fifth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_244" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=HiYDAwAGWud" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('244','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Yan, Shen; White, Colin; Savani, Yash; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=V8PcLz1NoQ0" title="OpenReview" target="blank">NAS-Bench-x11 and the Power of Learning Curves</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-Fifth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_245" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('245','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{yan2021nasbenchx,<br /> title = {NAS-Bench-x11 and the Power of Learning Curves},<br /> author = {Shen Yan and Colin White and Yash Savani and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Thirty-Fifth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_245" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=V8PcLz1NoQ0" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('245','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> White, Colin; Zela, Arber; Ru, Binxin; Liu, Yang; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=6RB77-6-_oI" title="OpenReview" target="blank">How Powerful are Performance Predictors in Neural Architecture Search?</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-Fifth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_243" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('243','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{white2021how,<br /> title = {How Powerful are Performance Predictors in Neural Architecture Search?},<br /> author = {Colin White and Arber Zela and Binxin Ru and Yang Liu and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Thirty-Fifth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_243" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=6RB77-6-_oI" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('243','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Kadra, Arlind; Lindauer, Marius; Hutter, Frank; Grabocka, Josif</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=d3k38LTDCyO" title="OpenReview" target="blank">Well-tuned Simple Nets Excel on Tabular Datasets</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-Fifth Conference on Neural Information Processing Systems, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_242" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('242','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{kadra2021welltuned,<br /> title = {Well-tuned Simple Nets Excel on Tabular Datasets},<br /> author = {Arlind Kadra and Marius Lindauer and Frank Hutter and Josif Grabocka},<br /> year = {2021},<br /> booktitle = {Thirty-Fifth Conference on Neural Information Processing Systems},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_242" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=d3k38LTDCyO" title="OpenReview" target="_blank">OpenReview</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('242','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg K H; Köhler, Gregor; Biedenkapp, André; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=hSjxQ3B7GWq" title="publication " target="blank">Sample-Efficient Automated Deep Reinforcement Learning</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">International Conference on Learning Representations (ICLR) 2021, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_57" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('57','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{franke-iclr21a,<br /> title = {Sample-Efficient Automated Deep Reinforcement Learning},<br /> author = {Jörg K H Franke and Gregor Köhler and André Biedenkapp and Frank Hutter},<br /> year = {2021},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2021},<br /> journal = {International Conference on Learning Representations (ICLR) 2021},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_57" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=hSjxQ3B7GWq" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/SEARL" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2009.01555" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38954141/sampleefficient-automated-deep-reinforcement-learning" title="video " target="_blank">video </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/blog-autorl/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('57','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zhang, Baohe; Rajan, Raghu; Pineda, Luis; Lambert, Nathan; Biedenkapp, André; Chua, Kurtland; Hutter, Frank; Calandra, Roberto</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-AISTATS-BO-MBRL.pdf" title="pdf " target="blank">On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS)'21, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_225" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('225','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{zhang-aistats21,<br /> title = {On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning},<br /> author = {Baohe Zhang and Raghu Rajan and Luis Pineda and Nathan Lambert and André Biedenkapp and Kurtland Chua and Frank Hutter and Roberto Calandra},<br /> year = {2021},<br /> booktitle = {Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS)'21},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_225" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-AISTATS-BO-MBRL.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://proceedings.mlr.press/v130/zhang21n.html" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/HPO_for_RL" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2102.13651" title="arXiv" target="_blank">arXiv</a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://www.youtube.com/watch?v=lH0mgnjr1v4" title="video " target="_blank">video </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://bair.berkeley.edu/blog/2021/04/19/mbrl/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('225','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Samuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://github.com/automl/trivialaugment" title="code " target="blank">TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICCV, </span><span class="tp_pub_additional_year">2021</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation (Top 3%)</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_152" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('152','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mueller-arxiv21a,<br /> title = {TrivialAugment: Tuning-free Yet State-of-the-Art Data Augmentation},<br /> author = {Samuel Müller and Frank Hutter},<br /> year = {2021},<br /> booktitle = {ICCV},<br /> journal = {arXiv:2103.10158 [cs.CV]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_152" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/trivialaugment" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2103.10158" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('152','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Ferreira, Fabio; Nierhoff, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-SynthEnvs-MetaAAAI.pdf" title="pdf " target="blank">Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">AAAI workshop on Meta-Learning Challenges, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_45" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('45','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{ferreira-metalearn21a,<br /> title = {Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies},<br /> author = {Fabio Ferreira and Thomas Nierhoff and Frank Hutter},<br /> year = {2021},<br /> booktitle = {AAAI workshop on Meta-Learning Challenges},<br /> journal = {AAAI workshop on Meta-Learning Challenges},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_45" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-SynthEnvs-MetaAAAI.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/learning_environments" title="code" target="_blank">code</a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://www.youtube.com/watch?v=upH4FCOXR3k" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('45','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Müller, Samuel; Biedenkapp, André; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/21-OAML-MetaAAAI.pdf" title="pdf " target="blank">In-Loop Meta-Learning with Gradient-Alignment Reward</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">AAAI workshop on Meta-Learning Challenges, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_153" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('153','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mueller-metalearn21a,<br /> title = {In-Loop Meta-Learning with Gradient-Alignment Reward},<br /> author = {Samuel Müller and André Biedenkapp and Frank Hutter},<br /> year = {2021},<br /> booktitle = {AAAI workshop on Meta-Learning Challenges},<br /> journal = {AAAI workshop on Meta-Learning Challenges},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_153" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/21-OAML-MetaAAAI.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://bit.ly/34K7aAT" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('153','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Souza, Artur; Nardi, Luigi; Oliveira, Leonardo; Olukotun, Kunle; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://2021.ecmlpkdd.org/wp-content/uploads/2021/07/sub_701.pdf" title="pdf" target="blank">Bayesian Optimization with a Prior for the Optimum</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_233" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('233','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{SouNar2021a,<br /> title = {Bayesian Optimization with a Prior for the Optimum},<br /> author = {Artur Souza and Luigi Nardi and Leonardo Oliveira and Kunle Olukotun and Marius Lindauer and Frank Hutter},<br /> year = {2021},<br /> booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_233" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://2021.ecmlpkdd.org/wp-content/uploads/2021/07/sub_701.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.14608" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('233','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Zimmer, Lucas; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1109/TPAMI.2021.3067763" title="Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL" target="blank">Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">IEEE Transactions on Pattern Analysis and Machine Intelligence, </span><span class="tp_pub_additional_pages">pp. 1-1, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_228" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('228','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{9382913,<br /> title = {Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL},<br /> author = {Lucas Zimmer and Marius Lindauer and Frank Hutter},<br /> doi = {10.1109/TPAMI.2021.3067763},<br /> year = {2021},<br /> journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},<br /> pages = {1-1},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_228" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://ieeexplore.ieee.org/document/9382913" title="IEEE" target="_blank">IEEE</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/Auto-PyTorch" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.13799" title="arXiv" target="_blank">arXiv</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1109/TPAMI.2021.3067763" title="Follow DOI:10.1109/TPAMI.2021.3067763" target="_blank">doi:10.1109/TPAMI.2021.3067763</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('228','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; van Rijn, Jan N; Kadra, Arlind; Gijsbers, Pieter; Mallik, Neeratyoy; Ravi, Sahithya; Müller, Andreas; Vanschoren, Joaquin; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://jmlr.org/papers/v22/19-920.html" title="publication " target="blank">OpenML-Python: an extensible Python API for OpenML</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Machine Learning Research, </span><span class="tp_pub_additional_volume">vol. 22, </span><span class="tp_pub_additional_number">no. 100, </span><span class="tp_pub_additional_pages">pp. 1-5, </span><span class="tp_pub_additional_year">2021</span>.</p><div class="tp_bibtex" id="tp_bibtex_53" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('53','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{feurer-jmlr21a,<br /> title = {OpenML-Python: an extensible Python API for OpenML},<br /> author = {Matthias Feurer and Jan N van Rijn and Arlind Kadra and Pieter Gijsbers and Neeratyoy Mallik and Sahithya Ravi and Andreas Müller and Joaquin Vanschoren and Frank Hutter},<br /> year = {2021},<br /> journal = {Journal of Machine Learning Research},<br /> volume = {22},<br /> number = {100},<br /> pages = {1-5},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_53" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jmlr.org/papers/v22/19-920.html" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/openml/openml-python/" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1911.02490" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('53','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2020">2020</h3> </td> </tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Awad, Noor; Shala, Gresa; Deng, Difan; Mallik, Neeratyoy; Feurer, Matthias; Eggensperger, Katharina; Biedenkapp, André; Vermetten, Diederick; Wang, Hao; Doerr, Carola; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://github.com/automl/Squirrel-Optimizer-BBO-NeurIPS20-automlorg" title="code " target="blank">Squirrel: A Switching Hyperparameter Optimizer Description of the entry by AutoML.org & IOHprofiler to the NeurIPS 2020 BBO challenge</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2012.08180 [cs.LG], </span><span class="tp_pub_additional_year">2020</span><span class="tp_pub_additional_note">, (Optimizer description for the <a href="https://bbochallenge.com/leaderboard" target="_blank">NeurIPS 2020 BBO competition</a>. <mark>Squirrel won the competition´s warm-starting friendly <a href="https://bbochallenge.com/altleaderboard" target="_blank">leaderboard</a></mark>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_2" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('2','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{awad-arxiv20a,<br /> title = {Squirrel: A Switching Hyperparameter Optimizer Description of the entry by AutoML.org & IOHprofiler to the NeurIPS 2020 BBO challenge},<br /> author = {Noor Awad and Gresa Shala and Difan Deng and Neeratyoy Mallik and Matthias Feurer and Katharina Eggensperger and André Biedenkapp and Diederick Vermetten and Hao Wang and Carola Doerr and Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> journal = {arXiv:2012.08180 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_2" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/Squirrel-Optimizer-BBO-NeurIPS20-automlorg" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2012.08180" title="arXiv " target="_blank">arXiv </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://bbochallenge.com/virtualroom" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('2','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-JMLR-BPSRNAS.pdf" title="pdf " target="blank">Best Practices for Scientific Research on Neural Architecture Search</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Machine Learning Research, </span><span class="tp_pub_additional_volume">vol. 21, </span><span class="tp_pub_additional_number">no. 243, </span><span class="tp_pub_additional_pages">pp. 1-18, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_133" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('133','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lindauer-jmlr20a,<br /> title = {Best Practices for Scientific Research on Neural Architecture Search},<br /> author = {Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> journal = {Journal of Machine Learning Research},<br /> volume = {21},<br /> number = {243},<br /> pages = {1-18},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_133" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-JMLR-BPSRNAS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-JMLR-BPSRNAS-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jmlr.org/papers/v21/20-056.html" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1909.02453" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('133','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lukasik, Jovita; Friede, David; Zela, Arber; Stuckenschmidt, Heiner; Hutter, Frank; Keuper, Margret</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-ARXIV-SVGe.pdf" title="pdf " target="blank">Smooth Variational Graph Embeddings for Efficient Neural Architecture Search</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2010.04683 [cs.LG], </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_146" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('146','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lukasik20,<br /> title = {Smooth Variational Graph Embeddings for Efficient Neural Architecture Search},<br /> author = {Jovita Lukasik and David Friede and Arber Zela and Heiner Stuckenschmidt and Frank Hutter and Margret Keuper},<br /> year = {2020},<br /> journal = {arXiv:2010.04683 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_146" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ARXIV-SVGe.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2010.04683" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('146','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Siems, Julien; Zimmer, Lucas; Zela, Arber; Lukasik, Jovita; Keuper, Margret; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-NIPS_WML-NB301.pdf" title="pdf " target="blank">NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">NeurIPS 4th Workshop on Meta-Learning, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_184" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('184','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{siems20,<br /> title = {NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search},<br /> author = {Julien Siems and Lucas Zimmer and Arber Zela and Jovita Lukasik and Margret Keuper and Frank Hutter},<br /> year = {2020},<br /> journal = {NeurIPS 4th Workshop on Meta-Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_184" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-NB301.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-NB301-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-NB301-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://meta-learn.github.io/2020/papers/50_paper.pdf" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/nasbench301" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2008.09777" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('184','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Souza, Artur; Nardi, Luigi; Oliveira, Leonardo B; Olukotun, Kunle; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-NIPS_WML-PBO.pdf" title="pdf " target="blank">Prior-guided Bayesian Optimization</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">NeurIPS 4th Workshop on Meta-Learning, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_186" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('186','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{souza-nipswml20a,<br /> title = {Prior-guided Bayesian Optimization},<br /> author = {Artur Souza and Luigi Nardi and Leonardo B Oliveira and Kunle Olukotun and Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> booktitle = {NeurIPS 4th Workshop on Meta-Learning},<br /> journal = {NeurIPS 4th Workshop on Meta-Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_186" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-PBO.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-PBO-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-PBO-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://meta-learn.github.io/2020/papers/63_paper.pdf" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.14608" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('186','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Speck, David; Biedenkapp, André; Hutter, Frank; Mattmüller, Robert; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="blank">Learning Heuristic Selection with Dynamic Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL@ICAPS'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_188" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('188','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{speck-prl20,<br /> title = {Learning Heuristic Selection with Dynamic Algorithm Configuration},<br /> author = {David Speck and André Biedenkapp and Frank Hutter and Robert Mattmüller and Marius Lindauer},<br /> year = {2020},<br /> booktitle = {Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL@ICAPS'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_188" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/speckdavid/rl-plan" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.08246v2" title="arXiv " target="_blank">arXiv </a></li><li><i class="fas fa-file-video"></i><a class="tp_pub_list" href="http://www2.informatik.uni-freiburg.de/~speckd/prl_presentation_13.mp4" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('188','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Stoll, Danny; Franke, Jörg K H; Wagner, Diane; Selg, Simon; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-NIPS_WML-HTADA.pdf" title="pdf " target="blank">Hyperparameter Transfer Across Developer Adjustments</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">NeurIPS 4th Workshop on Meta-Learning, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_190" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('190','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{stoll2020,<br /> title = {Hyperparameter Transfer Across Developer Adjustments},<br /> author = {Danny Stoll and Jörg K H Franke and Diane Wagner and Simon Selg and Frank Hutter},<br /> year = {2020},<br /> journal = {NeurIPS 4th Workshop on Meta-Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_190" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-HTADA.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-HTADA-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NIPS_WML-HTADA-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/hp-transfer/htaa_experiments" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('190','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Liu, Zhengying; Pavao, Adrien; Xu, Zhen; Escalera, Sergio; Ferreira, Fabio; Guyon, Isabelle; Hong, Sirui; Hutter, Frank; Ji, Rongrong; Junior, Julio C S Jacques; Li, Ge; Lindauer, Marius; Luo, Zhipeng; Madadi, Meysam; Nierhoff, Thomas; Niu, Kangning; Pan, Chunguang; Stoll, Danny; Treguer, Sebastien; Wang, Jin; Wang, Peng; Wu, Chenglin; Xiong, Youcheng; Zela, Arber; Zhang, Yang</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1109/TPAMI.2021.3075372" title="Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019" target="blank">Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">IEEE Transactions on Pattern Analysis and Machine Intelligence, </span><span class="tp_pub_additional_volume">vol. 43, </span><span class="tp_pub_additional_number">no. 9, </span><span class="tp_pub_additional_pages">pp. 3108-3125, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_139" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('139','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{Liu20,<br /> title = {Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019},<br /> author = {Zhengying Liu and Adrien Pavao and Zhen Xu and Sergio Escalera and Fabio Ferreira and Isabelle Guyon and Sirui Hong and Frank Hutter and Rongrong Ji and Julio C S Jacques Junior and Ge Li and Marius Lindauer and Zhipeng Luo and Meysam Madadi and Thomas Nierhoff and Kangning Niu and Chunguang Pan and Danny Stoll and Sebastien Treguer and Jin Wang and Peng Wang and Chenglin Wu and Youcheng Xiong and Arber Zela and Yang Zhang},<br /> doi = {10.1109/TPAMI.2021.3075372},<br /> year = {2020},<br /> journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},<br /> volume = {43},<br /> number = {9},<br /> pages = {3108-3125},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_139" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ARXIV-AutoDL.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://ieeexplore.ieee.org/document/941512" title="pdf (IEEE)" target="_blank">pdf (IEEE)</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1109/TPAMI.2021.3075372" title="Follow DOI:10.1109/TPAMI.2021.3075372" target="_blank">doi:10.1109/TPAMI.2021.3075372</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('139','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Shala, Gresa; Biedenkapp, André; Awad, Noor; Adriaensen, Steven; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-PPSN-LTO-CMA.pdf" title="pdf " target="blank">Learning Step-Size Adaptation in CMA-ES</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_183" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('183','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{shala-ppsn20,<br /> title = {Learning Step-Size Adaptation in CMA-ES},<br /> author = {Gresa Shala and André Biedenkapp and Noor Awad and Steven Adriaensen and Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> booktitle = {Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_183" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-PPSN-LTO-CMA.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-PPSN-LTO-CMA-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/LTO-CMA" title="code" target="_blank">code</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/file/d/1bhrbdUu-U76iJJtKYhPV3sdo4nI6N6XO/view?usp=sharing" title="video " target="_blank">video </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/learning-step-size-adaptation-in-cma-es/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('183','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Haase, Kai; Müller, Philipp; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/2009.13828" title="arXiv" target="blank">Neural Model-based Optimization with Right-Censored Observations</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2009:13828 [cs.AI], </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_24" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('24','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{eggensperger-arxiv20a,<br /> title = {Neural Model-based Optimization with Right-Censored Observations},<br /> author = {Katharina Eggensperger and Kai Haase and Philipp Müller and Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> journal = {arXiv:2009:13828 [cs.AI]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_24" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2009.13828" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('24','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Rajan, Raghu; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-BIG-TempoRL.pdf" title="pdf " target="blank">Towards TempoRL: Learning When to Act</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_9" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('9','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-bigicml20,<br /> title = {Towards TempoRL: Learning When to Act},<br /> author = {André Biedenkapp and Raghu Rajan and Frank Hutter and Marius Lindauer},<br /> year = {2020},<br /> booktitle = {Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_9" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-BIG-TempoRL.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-BIG-TempoRL-slides.pdf" title="slides " target="_blank">slides </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/TabularTempoRL" title="code " target="_blank">code </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38931281/towards-temporl" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('9','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eimer, Theresa; Biedenkapp, André; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-BIG-SPaCE.pdf" title="pdf " target="blank">Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_31" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('31','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eimer-bigicml20,<br /> title = {Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning},<br /> author = {Theresa Eimer and André Biedenkapp and Frank Hutter and Marius Lindauer},<br /> year = {2020},<br /> booktitle = {Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_31" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-BIG-SPaCE.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/SPaCE" title="code " target="_blank">code </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://biases-invariances-generalization.github.io/program/big_37.html" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('31','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Bozkurt, Furkan H; Eimer, Theresa; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-ECAI-DAC.pdf" title="pdf " target="blank">Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-fourth European Conference on Artificial Intelligence (ECAI'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_11" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('11','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-ecai20,<br /> title = {Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework},<br /> author = {André Biedenkapp and Furkan H Bozkurt and Theresa Eimer and Frank Hutter and Marius Lindauer},<br /> year = {2020},<br /> booktitle = {Proceedings of the Twenty-fourth European Conference on Artificial Intelligence (ECAI'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_11" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ECAI-DAC.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://ecai2020.eu/papers/1237_paper.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/DAC" title="code " target="_blank">code </a></li><li><i class="fab fa-youtube"></i><a class="tp_pub_list" href="https://youtu.be/wxPYtSGT05s" title="video " target="_blank">video </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/dynamic-algorithm-configuration/" title="blog" target="_blank">blog</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('11','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Zaidi, Sheheryar; Zela, Arber; Elsken, Thomas; Holmes, Chris; Hutter, Frank; Teh, Yee Whye</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-ARXIV-NES.pdf" title="pdf " target="blank">Neural Ensemble Search for Performant and Calibrated Predictions</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Workshop on Uncertainty and Robustness in Deep Learning (UDL@ICML`20), </span><span class="tp_pub_additional_year">2020</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_221" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('221','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{zaidi20,<br /> title = {Neural Ensemble Search for Performant and Calibrated Predictions},<br /> author = {Sheheryar Zaidi and Arber Zela and Thomas Elsken and Chris Holmes and Frank Hutter and Yee Whye Teh},<br /> year = {2020},<br /> journal = {Workshop on Uncertainty and Robustness in Deep Learning (UDL@ICML`20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_221" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ARXIV-NES.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ARXIV-NES-slides.pdf" title="slides " target="_blank">slides </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/nes" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.08573" title="arXiv https://slideslive.com/38930582/naural-ensemble-search-for-performant-and-[...]" target="_blank">arXiv https://slideslive.com/38930582/naural-ensemble-search-for-performant-and-[...]</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('221','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Staffler, Benedikt; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/20-CVPR-MetaNAS.pdf" title="pdf " target="blank">Meta-Learning of Neural Architectures for Few-Shot Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), </span><span class="tp_pub_additional_year">2020</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation (Top 6%)</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_37" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('37','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Elsken_2020_CVPR,<br /> title = {Meta-Learning of Neural Architectures for Few-Shot Learning},<br /> author = {Thomas Elsken and Benedikt Staffler and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2020},<br /> booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_37" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-CVPR-MetaNAS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://openaccess.thecvf.com/content_CVPR_2020/html/Elsken_Meta-Learning_of_Neural_Architectures_for_Few-Shot_Learning_CVPR_2020_paper.html" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1911.11090" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('37','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Gargiani, Matilde; Zanelli, Andrea; Diehl, Moritz; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://github.com/gmatilde/SGN" title="code " target="blank">On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2006.02409 [cs.LG], </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_63" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('63','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{gargiani-arxiv20a,<br /> title = {On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs},<br /> author = {Matilde Gargiani and Andrea Zanelli and Moritz Diehl and Frank Hutter},<br /> year = {2020},<br /> journal = {arXiv:2006.02409 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_63" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/gmatilde/SGN" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.02409" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('63','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Zimmer, Lucas; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://github.com/automl/Auto-PyTorch" title="code " target="blank">Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:2006.13799 [cs.LG], </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_231" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('231','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{zimmer-arxiv20,<br /> title = {Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL},<br /> author = {Lucas Zimmer and Marius Lindauer and Frank Hutter},<br /> year = {2020},<br /> journal = {arXiv:2006.13799 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_231" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/Auto-PyTorch" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2006.13799" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('231','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lehman, J; Clune, J; Misevic, D; Adami, C; Beaulieu, J; Bentley, P J; Bernard, S; Beslon, G; Bryson, D M; Chrabaszcz, P; Cheney, N; Cully, A; Doncieux, S; Dyer, F C; Ellefsen, K O; Feldt, R; Fischer, S; Forrest, S; Frénoy, A; Gagné, C; Goff, Le L K; Grabowski, L M; Hodjat, B; Hutter, F; Keller, L; Knibbe, C; Krcah, P; Lenski, R E; Lipson, H; MacCurdy, R; Maestre, C; Miikkulainen, R; Mitri, S; Moriarty, D E; Mouret, J -B; Nguyen, A; Ofria, C; Parizeau, M; Parsons, D P; Pennock, R T; Punch, W F; Ray, T S; Schoenauer, M; Shulte, E; Sims, K; Stanley, K O; Taddei, F; Tarapore, D; Thibault, S; Weimer, W; Watson, R; Yosinksi, J</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1162/artl_a_00319" title="The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities" target="blank">The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Artificial Life, </span><span class="tp_pub_additional_volume">vol. 26, </span><span class="tp_pub_additional_number">no. 2, </span><span class="tp_pub_additional_pages">pp. 274-306, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_20" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('20','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{DBLP:journals/corr/abs-1803-03453,<br /> title = {The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities},<br /> author = {J Lehman and J Clune and D Misevic and C Adami and J Beaulieu and P J Bentley and S Bernard and G Beslon and D M Bryson and P Chrabaszcz and N Cheney and A Cully and S Doncieux and F C Dyer and K O Ellefsen and R Feldt and S Fischer and S Forrest and A Frénoy and C Gagné and Le L K Goff and L M Grabowski and B Hodjat and F Hutter and L Keller and C Knibbe and P Krcah and R E Lenski and H Lipson and R MacCurdy and C Maestre and R Miikkulainen and S Mitri and D E Moriarty and J -B Mouret and A Nguyen and C Ofria and M Parizeau and D P Parsons and R T Pennock and W F Punch and T S Ray and M Schoenauer and E Shulte and K Sims and K O Stanley and F Taddei and D Tarapore and S Thibault and W Weimer and R Watson and J Yosinksi},<br /> doi = {10.1162/artl_a_00319},<br /> year = {2020},<br /> journal = {Artificial Life},<br /> volume = {26},<br /> number = {2},<br /> pages = {274-306},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_20" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://direct.mit.edu/artl/article/26/2/274/93255/The-Surprising-Creativity-of-Digital-Evolution-A" title="publication" target="_blank">publication</a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1803.03453" title="arXiv" target="_blank">arXiv</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1162/artl_a_00319" title="Follow DOI:10.1162/artl_a_00319" target="_blank">doi:10.1162/artl_a_00319</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('20','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Awad, Noor; Mallik, Neeratyoy; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/2020_DE_NAS-9.pdf" title="paper" target="blank">Differential Evolution for Neural Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 1st workshop on neural architecture search(@ICLR'20), </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_3" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('3','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{awad-iclr20,<br /> title = {Differential Evolution for Neural Architecture Search},<br /> author = {Noor Awad and Neeratyoy Mallik and F Hutter},<br /> year = {2020},<br /> booktitle = {Proceedings of the 1st workshop on neural architecture search(@ICLR'20)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_3" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ml.informatik.uni-freiburg.de/wp-content/uploads/2024/10/2020_DE_NAS-9.pdf" title="paper" target="_blank">paper</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-NASICLR-DE-NAS-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/DE-NAS" title="code " target="_blank">code </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://slideslive.com/38926388/differential-evolution-for-neural-architecture-search" title="videoundefined" target="_blank">videoundefined</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('3','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Tomašev, Nenad; Cornebise, Julien; Hutter, Frank; Mohamed, Shakir; Khan, Mohammad Emtiyaz; Winne, Ruben De; Schaul, Tom; Clopath, Claudia</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.nature.com/articles/s41467-020-15871-z" title="arXiv" target="blank">AI for social good: unlocking the opportunity for positive impact</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Nature Communications, </span><span class="tp_pub_additional_volume">vol. 11, </span><span class="tp_pub_additional_number">no. 1, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_193" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('193','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{tomavsev2020ai,<br /> title = {AI for social good: unlocking the opportunity for positive impact},<br /> author = {Nenad Tomašev and Julien Cornebise and Frank Hutter and Shakir Mohamed and Mohammad Emtiyaz Khan and Ruben De Winne and Tom Schaul and Claudia Clopath},<br /> year = {2020},<br /> journal = {Nature Communications},<br /> volume = {11},<br /> number = {1},<br /> publisher = {Nature Publishing Group},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_193" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.nature.com/articles/s41467-020-15871-z" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('193','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Volpp, Michael; Fröhlich, Lukas P; Fischer, Kirsten; Doerr, Andreas; Falkner, Stefan; Hutter, Frank; Daniel, Christian</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=ryeYpJSKwr" title="publication " target="blank">Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_205" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('205','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Volpp2020Meta-Learning,<br /> title = {Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization},<br /> author = {Michael Volpp and Lukas P Fröhlich and Kirsten Fischer and Andreas Doerr and Stefan Falkner and Frank Hutter and Christian Daniel},<br /> year = {2020},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_205" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=ryeYpJSKwr" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/boschresearch/MetaBO" title="code https://openreview.net/forum?id=ryeYpJSKwr" target="_blank">code https://openreview.net/forum?id=ryeYpJSKwr</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('205','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zela, Arber; Siems, Julien; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=SJx9ngStPH" title="publication " target="blank">NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_223" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('223','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Zela2020NAS-Bench-1Shot1:,<br /> title = {NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search},<br /> author = {Arber Zela and Julien Siems and Frank Hutter},<br /> year = {2020},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_223" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=SJx9ngStPH" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ICLR-NasBench1Shot1.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ICLR-NasBench1Shot1-slides.pdf" title="slides https://openreview.net/forum?id=SJx9ngStPH" target="_blank">slides https://openreview.net/forum?id=SJx9ngStPH</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/nasbench-1shot1" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/2001.10422" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('223','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zela, Arber; Elsken, Thomas; Saikia, Tonmoy; Marrakchi, Yassine; Brox, Thomas; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=H1gDNyrKDS" title="publication " target="blank">Understanding and Robustifying Differentiable Architecture Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2020</span><span class="tp_pub_additional_note">, (<mark>Oral Presentation (Top 7%)</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_224" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('224','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Zela2020Understanding,<br /> title = {Understanding and Robustifying Differentiable Architecture Search},<br /> author = {Arber Zela and Thomas Elsken and Tonmoy Saikia and Yassine Marrakchi and Thomas Brox and Frank Hutter},<br /> year = {2020},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_224" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=H1gDNyrKDS" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ICLR-RobustDARTS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/20-ICLR-RobustDARTS-slides.pdf" title="slides https://openreview.net/forum?id=H1gDNyrKDS" target="_blank">slides https://openreview.net/forum?id=H1gDNyrKDS</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/RobustDARTS" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1909.09656" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('224','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Gargiani, Matilde; Zanelli, Andrea; Tran-Dinh, Quoc; Diehl, Moritz; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/pdf?id=S1gEIerYwH" title="publication https://openreview.net/pdf?id=S1gEIerYwH" target="blank">Transferring Optimally Across Data Distrutions via Homotopy Methods</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2020</span>.</p><div class="tp_bibtex" id="tp_bibtex_64" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('64','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Gargiani2020TransferringOptimally,<br /> title = {Transferring Optimally Across Data Distrutions via Homotopy Methods},<br /> author = {Matilde Gargiani and Andrea Zanelli and Quoc Tran-Dinh and Moritz Diehl and Frank Hutter},<br /> year = {2020},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_64" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/pdf?id=S1gEIerYwH" title="publication https://openreview.net/pdf?id=S1gEIerYwH" target="_blank">publication https://openreview.net/pdf?id=S1gEIerYwH</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('64','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2019">2019</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Rajan, Raghu; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-NeurIPS-Workshop-MDP_Playground.pdf" title="pdf " target="blank">MDP Playground: Meta-Features in Reinforcement Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS 2019 Deep RL Workshop, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_160" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('160','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{rajan-neurips19,<br /> title = {MDP Playground: Meta-Features in Reinforcement Learning},<br /> author = {Raghu Rajan and Frank Hutter},<br /> year = {2019},<br /> booktitle = {NeurIPS 2019 Deep RL Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_160" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-NeurIPS-Workshop-MDP_Playground.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1909.07750v2" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('160','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1708.03731v2" title="arXiv" target="blank">OpenML Benchmarking Suites</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv, </span><span class="tp_pub_additional_volume">vol. 1708.0373v2, </span><span class="tp_pub_additional_pages">pp. 1-6, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_16" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('16','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{bischl-arxiv19a,<br /> title = {OpenML Benchmarking Suites},<br /> author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},<br /> year = {2019},<br /> journal = {arXiv},<br /> volume = {1708.0373v2},<br /> pages = {1-6},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_16" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1708.03731v2" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('16','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, Marius; Eggensperger, Katharina; Feurer, Matthias; Biedenkapp, André; Marben, Joshua; Müller, Philipp; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.ml4aad.org/boah/" title="project " target="blank">BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv:1908.06756 [cs.LG], </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_126" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('126','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lindauer-arxiv19,<br /> title = {BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters},<br /> author = {Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Joshua Marben and Philipp Müller and Frank Hutter},<br /> year = {2019},<br /> journal = {arXiv:1908.06756 [cs.LG]},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_126" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.ml4aad.org/boah/" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/BOAH" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1908.06756" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('126','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, Marius; Feurer, Matthias; Eggensperger, Katharina; Biedenkapp, André; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-DSO_BOBO-slides.pdf" title="slides " target="blank">Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">IJCAI 2019 DSO Workshop, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_130" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('130','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{lindauer-dso19,<br /> title = {Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters},<br /> author = {Marius Lindauer and Matthias Feurer and Katharina Eggensperger and André Biedenkapp and Frank Hutter},<br /> year = {2019},<br /> booktitle = {IJCAI 2019 DSO Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_130" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-DSO_BOBO-slides.pdf" title="slides " target="_blank">slides </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1908.06674" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('130','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Bozkurt, Furkan H; Hutter, Frank; Lindauer, Marius</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-DSO_White-Box-Benchmarks.pdf" title="pdf " target="blank">Towards White-box Benchmarks for Algorithm Control</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">IJCAI 2019 DSO Workshop, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_10" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('10','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-dso19,<br /> title = {Towards White-box Benchmarks for Algorithm Control},<br /> author = {André Biedenkapp and Furkan H Bozkurt and Frank Hutter and Marius Lindauer},<br /> year = {2019},<br /> booktitle = {IJCAI 2019 DSO Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_10" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-DSO_White-Box-Benchmarks.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.automl.org/automated-algorithm-design/dac" title="project " target="_blank">project </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1906.07644" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/2022/08/Whitebox@COSEAL_poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('10','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Fuks, L; Awad, Noor; Hutter, F; Lindauer, M</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-IJCAI_PEL.pdf" title="pdf" target="blank">An Evolution Strategy with Progressive Episode Lengths for Playing Games</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’19), </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_62" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('62','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{fuks-ijcai19a,<br /> title = {An Evolution Strategy with Progressive Episode Lengths for Playing Games},<br /> author = {L Fuks and Noor Awad and F Hutter and M Lindauer},<br /> year = {2019},<br /> booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’19)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_62" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-IJCAI_PEL.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('62','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Gargiani, M; Klein, A; Falkner, S; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.automl.org/wp-content/uploads/2019/06/automlws2019_Paper24.pdf" title="publication " target="blank">Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">6th ICML Workshop on Automated Machine Learning, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_65" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('65','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Gargiani6automl,<br /> title = {Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings},<br /> author = {M Gargiani and A Klein and S Falkner and F Hutter},<br /> year = {2019},<br /> booktitle = {6th ICML Workshop on Automated Machine Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_65" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://www.automl.org/wp-content/uploads/2019/06/automlws2019_Paper24.pdf" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/gmatilde/vdrnn" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('65','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_1.pdf" title="publication " target="blank">Hyperparameter Optimization</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): <span class="tp_pub_additional_booktitle">AutoML: Methods, Sytems, Challenges, </span><span class="tp_pub_additional_pages">pp. 3–33, </span><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_51" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('51','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{feurer-automlbook19a,<br /> title = {Hyperparameter Optimization},<br /> author = {Matthias Feurer and Frank Hutter},<br /> editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},<br /> year = {2019},<br /> booktitle = {AutoML: Methods, Sytems, Challenges},<br /> pages = {3--33},<br /> publisher = {Springer},<br /> chapter = {1},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_51" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_1.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://www.automl.org/wp-content/uploads/2018/09/chapter1-hpo.pdf" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('51','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost; Blum, Manuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/10.1007/978-3-030-05318-5_6" title="Auto-sklearn: Efficient and Robust Automated Machine Learning" target="blank">Auto-sklearn: Efficient and Robust Automated Machine Learning</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): <span class="tp_pub_additional_booktitle">AutoML: Methods, Systems, Challenges, </span><span class="tp_pub_additional_pages">pp. 113–134, </span><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_52" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('52','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{feurer-automlbook19b,<br /> title = {Auto-sklearn: Efficient and Robust Automated Machine Learning},<br /> author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Springenberg and Manuel Blum and Frank Hutter},<br /> editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},<br /> doi = {10.1007/978-3-030-05318-5_6},<br /> year = {2019},<br /> booktitle = {AutoML: Methods, Systems, Challenges},<br /> pages = {113--134},<br /> publisher = {Springer},<br /> chapter = {6},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_52" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://link.springer.com/chapter/10.1007/978-3-030-05318-5_6" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/auto-sklearn" title="code " target="_blank">code </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://www.automl.org/wp-content/uploads/2019/05/AutoML_Book_Chapter6.pdf" title="arXiv" target="_blank">arXiv</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/10.1007/978-3-030-05318-5_6" title="Follow DOI:10.1007/978-3-030-05318-5_6" target="_blank">doi:10.1007/978-3-030-05318-5_6</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('52','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Mendoza, Hector; Klein, Aaron; Feurer, Matthias; Springenberg, Jost Tobias; Urban, Matthias; Burkart, Michael; Dippel, Max; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_7.pdf" title="publication " target="blank">Towards Automatically-Tuned Deep Neural Networks</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.): <span class="tp_pub_additional_booktitle">AutoML: Methods, Sytems, Challenges, </span><span class="tp_pub_additional_pages">pp. 135–149, </span><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_150" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('150','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{mendoza-automlbook19a,<br /> title = {Towards Automatically-Tuned Deep Neural Networks},<br /> author = {Hector Mendoza and Aaron Klein and Matthias Feurer and Jost Tobias Springenberg and Matthias Urban and Michael Burkart and Max Dippel and Marius Lindauer and Frank Hutter},<br /> editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},<br /> year = {2019},<br /> booktitle = {AutoML: Methods, Sytems, Challenges},<br /> pages = {135--149},<br /> publisher = {Springer},<br /> chapter = {7},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_150" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-05318-5_7.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://www.automl.org/wp-content/uploads/2018/09/chapter7-autonet.pdf" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('150','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-JMLR-NASSurvey.pdf" title="pdf " target="blank">Neural Architecture Search: A Survey</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Machine Learning Research, </span><span class="tp_pub_additional_volume">vol. 20, </span><span class="tp_pub_additional_number">no. 55, </span><span class="tp_pub_additional_pages">pp. 1-21, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_34" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('34','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{elsken-jmlr19a,<br /> title = {Neural Architecture Search: A Survey},<br /> author = {Thomas Elsken and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2019},<br /> journal = {Journal of Machine Learning Research},<br /> volume = {20},<br /> number = {55},<br /> pages = {1-21},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_34" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-JMLR-NASSurvey.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1808.05377" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('34','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://jair.org/index.php/jair/article/view/11420" title="publication " target="blank">Pitfalls and Best Practices in Algorithm Configuration</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research (JAIR), </span><span class="tp_pub_additional_volume">vol. 64, </span><span class="tp_pub_additional_pages">pp. 861–893, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_27" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('27','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{eggensperger-jair19a,<br /> title = {Pitfalls and Best Practices in Algorithm Configuration},<br /> author = {Katharina Eggensperger and Marius Lindauer and Frank Hutter},<br /> year = {2019},<br /> journal = {Journal of Artificial Intelligence Research (JAIR)},<br /> volume = {64},<br /> pages = {861--893},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_27" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://jair.org/index.php/jair/article/view/11420" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1705.06058" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('27','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, Aaron; Dai, Zhenwen; Hutter, Frank; Lawrence, Neil; Gonzalez, Javier</p><p class="tp_pub_title"><a class="tp_title_link" href="http://papers.nips.cc/paper/8857-meta-surrogate-benchmarking-for-hyperparameter-optimization.pdf" title="publication " target="blank">Meta-Surrogate Benchmarking for Hyperparameter Optimization</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Wallach, H; Larochelle, H; Beygelzimer, A; d' Alché-Buc, F; Fox, E; Garnett, R (Ed.): <span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems 32, </span><span class="tp_pub_additional_pages">pp. 6270–6280, </span><span class="tp_pub_additional_publisher">Curran Associates, Inc., </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_156" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('156','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{NIPS2019_8857,<br /> title = {Meta-Surrogate Benchmarking for Hyperparameter Optimization},<br /> author = {Aaron Klein and Zhenwen Dai and Frank Hutter and Neil Lawrence and Javier Gonzalez},<br /> editor = {H Wallach and H Larochelle and A Beygelzimer and F d' Alché-Buc and E Fox and R Garnett},<br /> year = {2019},<br /> booktitle = {Advances in Neural Information Processing Systems 32},<br /> pages = {6270--6280},<br /> publisher = {Curran Associates, Inc.},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_156" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://papers.nips.cc/paper/8857-meta-surrogate-benchmarking-for-hyperparameter-optimization.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://papers.nips.cc/paper/8857-meta-surrogate-benchmarking-for-hyperparameter-optimization.pdf" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('156','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Franke, Jörg KH; Köhler, Gregor; Awad, Noor; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19_ACN.pdf" title="pdf " target="blank">Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">NeurIPS 2019 Workshop on Meta-Learning, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_60" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('60','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{franke2019neural,<br /> title = {Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control},<br /> author = {Jörg KH Franke and Gregor Köhler and Noor Awad and Frank Hutter},<br /> year = {2019},<br /> journal = {NeurIPS 2019 Workshop on Meta-Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_60" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19_ACN.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://arxiv.org/pdf/1910.12824.pdf" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('60','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=ByME42AqK7" title="publication" target="blank">Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_36" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('36','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{elsken2019efficient,<br /> title = {Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution},<br /> author = {Thomas Elsken and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2019},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_36" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=ByME42AqK7" title="publication" target="_blank">publication</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/pdf?id=ByME42AqK7" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1804.09081" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('36','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_book"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Kotthoff, Lars; Vanschoren, Joaquin (Ed.)</p><p class="tp_pub_title"><a class="tp_title_link" href="https://doi.org/10.1007/978-3-030-05318-5_1" title="publication" target="blank">Automated Machine Learning - Methods, Systems, Challenges</a> <span class="tp_pub_type book">Book</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_109" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('109','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@book{hutter2019automated,<br /> title = {Automated Machine Learning - Methods, Systems, Challenges},<br /> editor = {Frank Hutter and Lars Kotthoff and Joaquin Vanschoren},<br /> year = {2019},<br /> publisher = {Springer},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_109" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://doi.org/10.1007/978-3-030-05318-5_1" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('109','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Runge, Frederic; Stoll, Danny; Falkner, Stefan; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-ICLR-Learning-Design-RNA.pdf" title="pdf " target="blank">Learning to Design RNA</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_172" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('172','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{runge2019learning,<br /> title = {Learning to Design RNA},<br /> author = {Frederic Runge and Danny Stoll and Stefan Falkner and Frank Hutter},<br /> year = {2019},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_172" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-ICLR-Learning-Design-RNA.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/learna" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1812.11951" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('172','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Loshchilov, Ilya; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://openreview.net/forum?id=Bkg6RiCqY7" title="publication https://openreview.net/pdf?id=Bkg6RiCqY7" target="blank">Decoupled Weight Decay Regularization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_143" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('143','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{loshchilov2019decoupled,<br /> title = {Decoupled Weight Decay Regularization},<br /> author = {Ilya Loshchilov and Frank Hutter},<br /> year = {2019},<br /> booktitle = {International Conference on Learning Representations},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_143" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openreview.net/forum?id=Bkg6RiCqY7" title="publication https://openreview.net/pdf?id=Bkg6RiCqY7" target="_blank">publication https://openreview.net/pdf?id=Bkg6RiCqY7</a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/loshchil/AdamW-and-SGDW" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1711.05101" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('143','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Ying, Chris; Klein, Aaron; Real, Esteban; Christiansen, Eric; Murphy, Kevin; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/19-ICML-NasBench101.pdf" title="pdf " target="blank">Nas-bench-101: Towards reproducible neural architecture search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Thirty-sixth International Conference on Machine Learning, </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_220" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('220','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{ying2019bench,<br /> title = {Nas-bench-101: Towards reproducible neural architecture search},<br /> author = {Chris Ying and Aaron Klein and Esteban Real and Eric Christiansen and Kevin Murphy and Frank Hutter},<br /> year = {2019},<br /> booktitle = {Thirty-sixth International Conference on Machine Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_220" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-ICML-NasBench101.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/google-research/nasbench" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1902.09635" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('220','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Saikia, T; Marrakchi, Y; Zela, A; Hutter, F; Brox, T</p><p class="tp_pub_title"><a class="tp_title_link" href="http://lmb.informatik.uni-freiburg.de/Publications/2019/SMB19" title="publication " target="blank">AutoDispNet: Improving Disparity Estimation With AutoML</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">IEEE International Conference on Computer Vision (ICCV), </span><span class="tp_pub_additional_year">2019</span>.</p><div class="tp_bibtex" id="tp_bibtex_173" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('173','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{saikia19autodispnet,<br /> title = {AutoDispNet: Improving Disparity Estimation With AutoML},<br /> author = {T Saikia and Y Marrakchi and A Zela and F Hutter and T Brox},<br /> year = {2019},<br /> booktitle = {IEEE International Conference on Computer Vision (ICCV)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_173" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://lmb.informatik.uni-freiburg.de/Publications/2019/SMB19" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/19-ICCV-AutoDispNet.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://openaccess.thecvf.com/content_ICCV_2019/html/Saikia_AutoDispNet_Improving_Disparity_Estimation_With_AutoML_ICCV_2019_paper.html" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1905.07443" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('173','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2018">2018</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-IJCAI-DistNet-slides.pdf" title="slides " target="blank">Neural Networks for Predicting Algorithm Runtime Distributions</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18), </span><span class="tp_pub_additional_pages">pp. 1442-1448, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_26" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('26','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eggensperger-ijcai18a,<br /> title = {Neural Networks for Predicting Algorithm Runtime Distributions},<br /> author = {Katharina Eggensperger and Marius Lindauer and Frank Hutter},<br /> year = {2018},<br /> booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18)},<br /> pages = {1442-1448},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_26" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-IJCAI-DistNet-slides.pdf" title="slides " target="_blank">slides </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-IJCAI-DistNet-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.ijcai.org/proceedings/2018/200" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1709.07615" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('26','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Zela, Arber; Klein, Aaron; Falkner, Stefan; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-AUTOML-EfficientNAS.pdf" title="pdf " target="blank">Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2018 AutoML Workshop, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_222" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('222','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{zela-automl18,<br /> title = {Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search},<br /> author = {Arber Zela and Aaron Klein and Stefan Falkner and Frank Hutter},<br /> year = {2018},<br /> booktitle = {ICML 2018 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_222" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-AUTOML-EfficientNAS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-AUTOML-EfficientNAS-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('222','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Chrabąszcz, Patryk; Loshchilov, Ilya; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-IJCAI-B2B.pdf" title="pdf " target="blank">Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, </span><span class="tp_pub_additional_pages">pp. 1419–1426, </span><span class="tp_pub_additional_publisher">International Joint Conferences on Artificial Intelligence Organization, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_18" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('18','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{chrabaszcz-ijcai18a,<br /> title = {Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari},<br /> author = {Patryk Chrabąszcz and Ilya Loshchilov and Frank Hutter},<br /> year = {2018},<br /> booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on <br /> Artificial Intelligence, IJCAI-18},<br /> pages = {1419--1426},<br /> publisher = {International Joint Conferences on Artificial Intelligence Organization},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_18" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-IJCAI-B2B.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.ijcai.org/proceedings/2018/197" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/PatrykChrabaszcz/Canonical_ES_Atari" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1802.08842" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('18','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Falkner, Stefan; Klein, Aaron; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-ICML-BOHB.pdf" title="pdf " target="blank">BOHB: Robust and Efficient Hyperparameter Optimization at Scale</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 35th International Conference on Machine Learning (ICML 2018), </span><span class="tp_pub_additional_pages">pp. 1436–1445, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_40" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('40','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{falkner-icml-18,<br /> title = {BOHB: Robust and Efficient Hyperparameter Optimization at Scale},<br /> author = {Stefan Falkner and Aaron Klein and Frank Hutter},<br /> year = {2018},<br /> booktitle = {Proceedings of the 35th International Conference on Machine Learning (ICML 2018)},<br /> pages = {1436--1445},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_40" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-ICML-BOHB.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-ICML-BOHB-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-ICML-BOHB-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://proceedings.mlr.press/v80/falkner18a.html" title="publication " target="_blank">publication </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/HpBandSter/tree/icml_2018" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('40','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Eggensperger, Katharina; Falkner, Stefan; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-AUTOML-AutoChallenge.pdf" title="pdf" target="blank">Practical Automated Machine Learning for the AutoML Challenge 2018</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2018 AutoML Workshop, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_49" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('49','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{feurer-automl18b,<br /> title = {Practical Automated Machine Learning for the AutoML Challenge 2018},<br /> author = {Matthias Feurer and Katharina Eggensperger and Stefan Falkner and Marius Lindauer and Frank Hutter},<br /> year = {2018},<br /> booktitle = {ICML 2018 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_49" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-AUTOML-AutoChallenge.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('49','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Schirrmeister, R; Chrabąszcz, P; Hutter, F; Ball, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-ICML-RevNets-poster.pdf" title="poster " target="blank">Training Generative Reversible Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_177" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('177','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{schirrmeister_revnets18,<br /> title = {Training Generative Reversible Networks},<br /> author = {R Schirrmeister and P Chrabąszcz and F Hutter and T Ball},<br /> year = {2018},<br /> booktitle = {ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_177" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-ICML-RevNets-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/robintibor/generative-reversible" title="code " target="_blank">code </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1806.01610" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('177','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, M; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-AUTOML-AutoAutoML.pdf" title="pdf" target="blank">Towards Further Automation in AutoML</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2018 AutoML Workshop, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_48" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('48','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{feurer-automl18a,<br /> title = {Towards Further Automation in AutoML},<br /> author = {M Feurer and F Hutter},<br /> year = {2018},<br /> booktitle = {ICML 2018 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_48" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-AUTOML-AutoAutoML.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('48','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Marben, Joshua; Lindauer, Marius; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-LION12-CAVE.pdf" title="pdf " target="blank">CAVE: Configuration Assessment, Visualization and Evaluation</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Conference on Learning and Intelligent Optimization (LION'18), </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_13" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('13','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-lion18a,<br /> title = {CAVE: Configuration Assessment, Visualization and Evaluation},<br /> author = {André Biedenkapp and Joshua Marben and Marius Lindauer and Frank Hutter},<br /> year = {2018},<br /> booktitle = {Proceedings of the International Conference on Learning and Intelligent Optimization (LION'18)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_13" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-LION12-CAVE.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-LION12-CAVE-slides.pdf" title="slides " target="_blank">slides </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.ml4aad.org/algorithm-analysis/cave/" title="project " target="_blank">project </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/CAVE" title="code" target="_blank">code</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://drive.google.com/open?id=1lNu6sZGB3lcr6fYI1tzLOJzILISO9WE1" title="video" target="_blank">video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('13','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1804.09081" title="arXiv" target="blank">Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">ArXiv e-prints, </span><span class="tp_pub_additional_volume">vol. 1804.09081, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_35" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('35','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{elsken-nas-arxiv18a,<br /> title = {Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution},<br /> author = {Thomas Elsken and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2018},<br /> journal = {ArXiv e-prints},<br /> volume = {1804.09081},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_35" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1804.09081" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('35','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Ilg, Eddy; Cicek, Oezguen; Galesso, Silvio; Klein, Aaron; Makansi, Osama; Hutter, Frank; Brox, Thomas</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/18-ARXIV-UncertaintyOpticalFlow.pdf" title="pdf " target="blank">Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Proceedings of ECCV 2018, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_115" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('115','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{ilg-arxiv18a,<br /> title = {Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks},<br /> author = {Eddy Ilg and Oezguen Cicek and Silvio Galesso and Aaron Klein and Osama Makansi and Frank Hutter and Thomas Brox},<br /> year = {2018},<br /> journal = {Proceedings of ECCV 2018},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_115" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/18-ARXIV-UncertaintyOpticalFlow.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/1802.07095" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('115','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/download/17235/15829" title="publication " target="blank">Warmstarting of Model-based Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the AAAI conference, </span><span class="tp_pub_additional_pages">pp. 1355–1362, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_124" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('124','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{lindauer-aaai18a,<br /> title = {Warmstarting of Model-based Algorithm Configuration},<br /> author = {M Lindauer and F Hutter},<br /> year = {2018},<br /> booktitle = {Proceedings of the AAAI conference},<br /> pages = {1355--1362},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_124" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/download/17235/15829" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1709.04636" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('124','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Lindauer, Marius; Hoos, Holger H; Hutter, Frank; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="https://link.springer.com/article/10.1007/s10994-017-5683-z" title="publication " target="blank">Efficient Benchmarking of Algorithm Configurators via Model-Based Surrogates</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Machine Learning, </span><span class="tp_pub_additional_volume">vol. 107, </span><span class="tp_pub_additional_pages">pp. 15-41, </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_28" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('28','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{eggensperger-ml18a,<br /> title = {Efficient Benchmarking of Algorithm Configurators via Model-Based Surrogates},<br /> author = {Katharina Eggensperger and Marius Lindauer and Holger H Hoos and Frank Hutter and Kevin Leyton-Brown},<br /> year = {2018},<br /> journal = {Machine Learning},<br /> volume = {107},<br /> pages = {15-41},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_28" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://link.springer.com/article/10.1007/s10994-017-5683-z" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1703.10342" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('28','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Wilson, Dennis; Rodrigues, Silvio; Segura, Carlos; Loshchilov, Ilya; Hutter, Frank; Buenfil, Guillermo López; Kheiri, Ahmed; Keedwell, Ed; Ocampo-Pineda, Mario; Özcan, Ender; Peña, Sergio Ivvan Valdez; Goldman, Brian; Rionda, Salvador Botello; Hernández-Aguirre, Arturo; Veeramachaneni, Kalyan; Cussat-Blanc, Sylvain</p><p class="tp_pub_title"><a class="tp_title_link" href="https://dx.doi.org/https://doi.org/10.1016/j.renene.2018.03.052" title="Evolutionary computation for wind farm layout optimization" target="blank">Evolutionary computation for wind farm layout optimization</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Renewable Energy, </span><span class="tp_pub_additional_volume">vol. 126, </span><span class="tp_pub_additional_pages">pp. 681 - 691, </span><span class="tp_pub_additional_year">2018</span>, <span class="tp_pub_additional_issn">ISSN: 0960-1481</span>.</p><div class="tp_bibtex" id="tp_bibtex_211" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('211','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{WILSON2018681,<br /> title = {Evolutionary computation for wind farm layout optimization},<br /> author = {Dennis Wilson and Silvio Rodrigues and Carlos Segura and Ilya Loshchilov and Frank Hutter and Guillermo López Buenfil and Ahmed Kheiri and Ed Keedwell and Mario Ocampo-Pineda and Ender Özcan and Sergio Ivvan Valdez Peña and Brian Goldman and Salvador Botello Rionda and Arturo Hernández-Aguirre and Kalyan Veeramachaneni and Sylvain Cussat-Blanc},<br /> doi = {https://doi.org/10.1016/j.renene.2018.03.052},<br /> year = {2018},<br /> issn = {0960-1481},<br /> journal = {Renewable Energy},<br /> volume = {126},<br /> pages = {681 - 691},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_211" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.sciencedirect.com/science/article/pii/S096014811830363X" title="publication" target="_blank">publication</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://dl.acm.org/citation.cfm?id=3205651.3208208" title="summary" target="_blank">summary</a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://dl.acm.org/downformats.cfm?id=3208208&parent_id=3205651&expformat=bibtex" title="summary bibtex" target="_blank">summary bibtex</a></li><li><i class="ai ai-doi"></i><a class="tp_pub_list" href="https://dx.doi.org/https://doi.org/10.1016/j.renene.2018.03.052" title="Follow DOI:https://doi.org/10.1016/j.renene.2018.03.052" target="_blank">doi:https://doi.org/10.1016/j.renene.2018.03.052</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('211','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Wilson, James; Hutter, Frank; Deisenroth, Marc</p><p class="tp_pub_title"><a class="tp_title_link" href="http://papers.nips.cc/paper/8194-maximizing-acquisition-functions-for-bayesian-optimization.pdf" title="publication " target="blank">Maximizing acquisition functions for Bayesian optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Bengio, S; Wallach, H; Larochelle, H; Grauman, K; Cesa-Bianchi, N; Garnett, R (Ed.): <span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems 31, </span><span class="tp_pub_additional_pages">pp. 9906–9917, </span><span class="tp_pub_additional_publisher">Curran Associates, Inc., </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_210" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('210','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{wilson-nips2018,<br /> title = {Maximizing acquisition functions for Bayesian optimization},<br /> author = {James Wilson and Frank Hutter and Marc Deisenroth},<br /> editor = {S Bengio and H Wallach and H Larochelle and K Grauman and N Cesa-Bianchi and R Garnett},<br /> year = {2018},<br /> booktitle = {Advances in Neural Information Processing Systems 31},<br /> pages = {9906--9917},<br /> publisher = {Curran Associates, Inc.},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_210" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://papers.nips.cc/paper/8194-maximizing-acquisition-functions-for-bayesian-optimization.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="http://papers.nips.cc/paper/8194-maximizing-acquisition-functions-for-bayesian-optimization.pdf" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('210','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author">van Rijn, J N; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="http://www.kdd.org/kdd2018/accepted-papers/view/hyperparameter-importance-across-datasets" title="publication " target="blank">Hyperparameter Importance Across Datasets</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), </span><span class="tp_pub_additional_year">2018</span>.</p><div class="tp_bibtex" id="tp_bibtex_161" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('161','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{Rijn-Arxiv2017,<br /> title = {Hyperparameter Importance Across Datasets},<br /> author = {J N van Rijn and F Hutter},<br /> year = {2018},<br /> journal = {SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_161" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.kdd.org/kdd2018/accepted-papers/view/hyperparameter-importance-across-datasets" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1710.04725" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('161','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2017">2017</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, A; Falkner, S; Mansur, N; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-BayesOpt-RoBO.pdf" title="pdf" target="blank">RoBO: A Flexible and Robust Bayesian Optimization Framework in Python</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS 2017 Bayesian Optimization Workshop, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_119" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('119','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{klein-bayesopt17,<br /> title = {RoBO: A Flexible and Robust Bayesian Optimization Framework in Python},<br /> author = {A Klein and S Falkner and N Mansur and F Hutter},<br /> year = {2017},<br /> booktitle = {NIPS 2017 Bayesian Optimization Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_119" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-BayesOpt-RoBO.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('119','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Falkner, S; Klein, A; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-BayesOpt-BOHB.pdf" title="pdf" target="blank">Combining Hyperband and Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS 2017 Bayesian Optimization Workshop, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_39" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('39','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{falkner-bayesopt17,<br /> title = {Combining Hyperband and Bayesian Optimization},<br /> author = {S Falkner and A Klein and F Hutter},<br /> year = {2017},<br /> booktitle = {NIPS 2017 Bayesian Optimization Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_39" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-BayesOpt-BOHB.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('39','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Elsken, Thomas; Metzen, Jan Hendrik; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-MTL-NAS.pdf" title="pdf " target="blank">Simple And Efficient Architecture Search for Convolutional Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS Workshop on Meta-Learning, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_38" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('38','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{elsken_nas_mtl17a,<br /> title = {Simple And Efficient Architecture Search for Convolutional Neural Networks},<br /> author = {Thomas Elsken and Jan Hendrik Metzen and Frank Hutter},<br /> year = {2017},<br /> booktitle = {NIPS Workshop on Meta-Learning},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_38" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-MTL-NAS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1711.04528" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('38','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Bischl, Bernd; Casalicchio, Giuseppe; Feurer, Matthias; Hutter, Frank; Lang, Michel; Mantovani, Rafael G; van Rijn, Jan N; Vanschoren, Joaquin</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1708.03731v1" title="arXiv" target="blank">OpenML Benchmarking Suites and the OpenML100</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">arXiv, </span><span class="tp_pub_additional_volume">vol. 1708.0373v1, </span><span class="tp_pub_additional_pages">pp. 1-6, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_15" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('15','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{bischl-arxiv17a,<br /> title = {OpenML Benchmarking Suites and the OpenML100},<br /> author = {Bernd Bischl and Giuseppe Casalicchio and Matthias Feurer and Frank Hutter and Michel Lang and Rafael G Mantovani and Jan N van Rijn and Joaquin Vanschoren},<br /> year = {2017},<br /> journal = {arXiv},<br /> volume = {1708.0373v1},<br /> pages = {1-6},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_15" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1708.03731v1" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('15','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Greff, K; Klein, A; Chovanec, M; Hutter, F; Schmidhuber, J</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-SciPy-Sacred.pdf" title="pdf" target="blank">The Sacred Infrastructure for Computational Research</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 15th Python in Science Conference (SciPy 2017), </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_70" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('70','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{greff-scipy17,<br /> title = {The Sacred Infrastructure for Computational Research},<br /> author = {K Greff and A Klein and M Chovanec and F Hutter and J Schmidhuber},<br /> year = {2017},<br /> booktitle = {Proceedings of the 15th Python in Science Conference (SciPy 2017)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_70" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-SciPy-Sacred.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('70','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hoos, H; Hutter, F; Schaub, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-IJCAI-AutoFolio.pdf" title="pdf" target="blank">AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17), </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_131" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('131','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{lindauer-ijcai17,<br /> title = {AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)},<br /> author = {M Lindauer and H Hoos and F Hutter and T Schaub},<br /> year = {2017},<br /> booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'17)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_131" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-IJCAI-AutoFolio.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('131','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Loshchilov, I; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-ICLR-SGDR.pdf" title="pdf" target="blank">SGDR: Stochastic Gradient Descent with Warm Restarts</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR) 2017 Conference Track, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_142" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('142','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{loshchilov-ICLR17SGDR,<br /> title = {SGDR: Stochastic Gradient Descent with Warm Restarts},<br /> author = {I Loshchilov and F Hutter},<br /> year = {2017},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2017 Conference Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_142" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-ICLR-SGDR.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('142','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, A; Falkner, S; Springenberg, J T; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-ICLR-LCNet.pdf" title="pdf" target="blank">Learning Curve Prediction with Bayesian Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR) 2017 Conference Track, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_121" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('121','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{klein-iclr17,<br /> title = {Learning Curve Prediction with Bayesian Neural Networks},<br /> author = {A Klein and S Falkner and J T Springenberg and F Hutter},<br /> year = {2017},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2017 Conference Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_121" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-ICLR-LCNet.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('121','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Wagner, M; Lindauer, M; Misir, M; Nallaperuma, S; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-JoH-TTP.pdf" title="pdf " target="blank">A case study of algorithm selection for the traveling thief problem</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Heuristics, </span><span class="tp_pub_additional_pages">pp. 1-26, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_207" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('207','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{wagner-joh17a,<br /> title = {A case study of algorithm selection for the traveling thief problem},<br /> author = {M Wagner and M Lindauer and M Misir and S Nallaperuma and F Hutter},<br /> year = {2017},<br /> journal = {Journal of Heuristics},<br /> pages = {1-26},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_207" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-JoH-TTP.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://link.springer.com/article/10.1007/s10732-017-9328-y" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('207','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Biedenkapp, André; Lindauer, Marius; Eggensperger, Katharina; Fawcett, Chris; Hoos, Holger H; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-AAAI-Surrogate-Ablation.pdf" title="pdf " target="blank">Efficient Parameter Importance Analysis via Ablation with Surrogates</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17), </span><span class="tp_pub_additional_pages">pp. 773–779, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_8" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('8','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{biedenkapp-aaai17a,<br /> title = {Efficient Parameter Importance Analysis via Ablation with Surrogates},<br /> author = {André Biedenkapp and Marius Lindauer and Katharina Eggensperger and Chris Fawcett and Holger H Hoos and Frank Hutter},<br /> year = {2017},<br /> booktitle = {Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17)},<br /> pages = {773--779},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_8" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-AAAI-Surrogate-Ablation.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-AAAI-Surrogate-Ablation-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://ojs.aaai.org/index.php/AAAI/article/view/10657" title="publication " target="_blank">publication </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://www.ml4aad.org/algorithm-analysis/efficient-ablation/" title="project " target="_blank">project </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://bitbucket.org/biedenka/ablation/src/master/" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('8','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Lindauer, M; Balint, A; Bayless, S; Hoos, H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="http://www.sciencedirect.com/science/article/pii/S0004370216301138" title="publication " target="blank">The Configurable SAT Solver Challenge (CSSC)</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Artificial Intelligence Journal (AIJ), </span><span class="tp_pub_additional_volume">vol. 243, </span><span class="tp_pub_additional_pages">pp. 1-25, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_104" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('104','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{hutter-aij17a,<br /> title = {The Configurable SAT Solver Challenge (CSSC)},<br /> author = {F Hutter and M Lindauer and A Balint and S Bayless and H Hoos and K Leyton-Brown},<br /> year = {2017},<br /> journal = {Artificial Intelligence Journal (AIJ)},<br /> volume = {243},<br /> pages = {1-25},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_104" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.sciencedirect.com/science/article/pii/S0004370216301138" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/1505.01221" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('104','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="http://drops.dagstuhl.de/opus/volltexte/2017/6956/" title="publication" target="blank">Pitfalls and Best Practices for Algorithm Configuration (Breakout Session Report)</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Dagstuhl Reports, </span><span class="tp_pub_additional_volume">vol. 6, </span><span class="tp_pub_additional_pages">pp. 70-72, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_128" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('128','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lindauer-dagstuhl17a,<br /> title = {Pitfalls and Best Practices for Algorithm Configuration (Breakout Session Report)},<br /> author = {M Lindauer and F Hutter},<br /> year = {2017},<br /> journal = {Dagstuhl Reports},<br /> volume = {6},<br /> pages = {70-72},<br /> publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_128" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://drops.dagstuhl.de/opus/volltexte/2017/6956/" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('128','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Schirrmeister, Robin; Springenberg, Jost Tobias; Fiederer, Lukas; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio</p><p class="tp_pub_title"><a class="tp_title_link" href="http://dx.doi.org/10.1002/hbm.23730" title="publication " target="blank">Deep learning with convolutional neural networks for EEG decoding and visualization</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Human Brain Mapping, </span><span class="tp_pub_additional_volume">vol. 38, </span><span class="tp_pub_additional_pages">pp. 5391–5420, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_175" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('175','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{schirrmeister-17a,<br /> title = {Deep learning with convolutional neural networks for EEG decoding and visualization},<br /> author = {Robin Schirrmeister and Jost Tobias Springenberg and Lukas Fiederer and Martin Glasstetter and Katharina Eggensperger and Michael Tangermann and Frank Hutter and Wolfram Burgard and Tonio Ball},<br /> year = {2017},<br /> journal = {Human Brain Mapping},<br /> volume = {38},<br /> pages = {5391--5420},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_175" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://dx.doi.org/10.1002/hbm.23730" title="publication " target="_blank">publication </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://onlinelibrary.wiley.com/doi/10.1002/hbm.23730/full" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1703.05051" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('175','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Chrabaszcz, Patryk; Loshchilov, Ilya; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="https://arxiv.org/abs/1707.08819" title="arXiv" target="blank">A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_257" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('257','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{chrabaszcz2017downsampled,<br /> title = {A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets},<br /> author = {Patryk Chrabaszcz and Ilya Loshchilov and Frank Hutter},<br /> year = {2017},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_257" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="https://arxiv.org/abs/1707.08819" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('257','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Wilson, James T.; Moriconi, Riccardo; Hutter, Frank; Deisenroth, Marc P.</p><p class="tp_pub_title"><a class="tp_title_link" href="https://bayesopt.github.io/papers/2017/32.pdf" title="pdf" target="blank">The Reparameterization Trick for Acquisition Functions</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS Workshop on Bayesian Optimization, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_256" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('256','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Wilson2017,<br /> title = {The Reparameterization Trick for Acquisition Functions},<br /> author = {James T. Wilson and Riccardo Moriconi and Frank Hutter and Marc P. Deisenroth},<br /> year = {2017},<br /> booktitle = {NIPS Workshop on Bayesian Optimization},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_256" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://bayesopt.github.io/papers/2017/32.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('256','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hoos, H; Hutter, F; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="https://ada.liacs.leidenuniv.nl/papers/LinEtAl18.pdf" title="pdf" target="blank">Selection and Configuration of Parallel Portfolios</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Hamadi, Y; Sais, L (Ed.): <span class="tp_pub_additional_booktitle">Handbook of Parallel Constraint Reasoning, </span><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_135" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('135','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{lindauer-parallel_ac_as17,<br /> title = {Selection and Configuration of Parallel Portfolios},<br /> author = {M Lindauer and H Hoos and F Hutter and K Leyton-Brown},<br /> editor = {Y Hamadi and L Sais},<br /> year = {2017},<br /> booktitle = {Handbook of Parallel Constraint Reasoning},<br /> publisher = {Springer},<br /> chapter = {15},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_135" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://ada.liacs.leidenuniv.nl/papers/LinEtAl18.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('135','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, A; Falkner, S; Bartels, S; Hennig, P; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-AISTATS-Fabolas.pdf" title="pdf " target="blank">Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the AISTATS conference, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_117" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('117','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{klein-aistats17,<br /> title = {Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets},<br /> author = {A Klein and S Falkner and S Bartels and P Hennig and F Hutter},<br /> year = {2017},<br /> booktitle = {Proceedings of the AISTATS conference},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_117" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-AISTATS-Fabolas.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/RoBO" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('117','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, A; Falkner, S; Bartels, S; Hennig, P; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-EJS-Fabolas.pdf" title="pdf" target="blank">Fast Bayesian hyperparameter optimization on large datasets</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Electronic Journal of Statistics, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_120" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('120','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{klein-ejs17,<br /> title = {Fast Bayesian hyperparameter optimization on large datasets},<br /> author = {A Klein and S Falkner and S Bartels and P Hennig and F Hutter},<br /> year = {2017},<br /> booktitle = {Electronic Journal of Statistics},<br /> volume = {11},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_120" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-EJS-Fabolas.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('120','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author">van Rijn, J N; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/17-AutoML-fanova.pdf" title="pdf" target="blank">An Empirical Study of Hyperparameter Importance Across Datasets</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms (AutoML 2017), </span><span class="tp_pub_additional_pages">pp. 97–104, </span><span class="tp_pub_additional_year">2017</span>.</p><div class="tp_bibtex" id="tp_bibtex_162" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('162','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{rijn-automl2017,<br /> title = {An Empirical Study of Hyperparameter Importance Across Datasets},<br /> author = {J N van Rijn and F Hutter},<br /> year = {2017},<br /> booktitle = {Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms (AutoML 2017)},<br /> volume = {1998},<br /> pages = {97--104},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_162" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/17-AutoML-fanova.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('162','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2016">2016</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Springenberg, J T; Klein, A; Falkner, S; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-NIPS-BOHamiANN.pdf" title="pdf " target="blank">Bayesian optimization with robust Bayesian neural networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems 29, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_189" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('189','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{springenberg-nips2016,<br /> title = {Bayesian optimization with robust Bayesian neural networks},<br /> author = {J T Springenberg and A Klein and S Falkner and F Hutter},<br /> year = {2016},<br /> booktitle = {Advances in Neural Information Processing Systems 29},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_189" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-NIPS-BOHamiANN.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-NIPS-BOHamiANN-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/automl/RoBO" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('189','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Bischl, B; Kerschke, P; Kotthoff, L; Lindauer, M; Malitsky, Y; Frechétte, A; Hoos, H; Hutter, F; Leyton-Brown, K; Tierney, K; Vanschoren, J</p><p class="tp_pub_title"><a class="tp_title_link" href="http://www.sciencedirect.com/science/article/pii/S0004370216300388" title="publication " target="blank">ASlib: A Benchmark Library for Algorithm Selection</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Artificial Intelligence Journal (AIJ), </span><span class="tp_pub_additional_volume">vol. 237, </span><span class="tp_pub_additional_pages">pp. 41-58, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_14" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('14','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{bischl-aij16a,<br /> title = {ASlib: A Benchmark Library for Algorithm Selection},<br /> author = {B Bischl and P Kerschke and L Kotthoff and M Lindauer and Y Malitsky and A Frechétte and H Hoos and F Hutter and K Leyton-Brown and K Tierney and J Vanschoren},<br /> year = {2016},<br /> journal = {Artificial Intelligence Journal (AIJ)},<br /> volume = {237},<br /> pages = {41-58},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_14" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://www.sciencedirect.com/science/article/pii/S0004370216300388" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/1506.02465" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('14','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Mendoza, H; Klein, A; Feurer, M; Springenberg, J; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-AUTOML-AutoNet.pdf" title="pdf " target="blank">Towards Automatically-Tuned Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2016 AutoML Workshop, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_149" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('149','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{mendoza-automl16a,<br /> title = {Towards Automatically-Tuned Neural Networks},<br /> author = {H Mendoza and A Klein and M Feurer and J Springenberg and F Hutter},<br /> year = {2016},<br /> booktitle = {ICML 2016 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_149" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-AUTOML-AutoNet.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-AUTOML-AutoNet-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('149','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Loshchilov, I; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-ICLR-BatchSelection.pdf" title="pdf " target="blank">Online Batch Selection for Faster Training of Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR) 2016 Workshop Track, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_140" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('140','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{loshchilov-ICLR16batchsel,<br /> title = {Online Batch Selection for Faster Training of Neural Networks},<br /> author = {I Loshchilov and F Hutter},<br /> year = {2016},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2016 Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_140" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-ICLR-BatchSelection.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://sites.google.com/site/batchsel/" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('140','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Loshchilov, I; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="https://sites.google.com/site/cmaesfordnn/" title="code" target="blank">CMA-ES for Hyperparameter Optimization of Deep Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Learning Representations (ICLR) 2016 Workshop Track, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_141" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('141','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{loshchilov-ICLR16hyperparam,<br /> title = {CMA-ES for Hyperparameter Optimization of Deep Neural Networks},<br /> author = {I Loshchilov and F Hutter},<br /> year = {2016},<br /> booktitle = {International Conference on Learning Representations (ICLR) 2016 Workshop Track},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_141" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://sites.google.com/site/cmaesfordnn/" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('141','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Wang, Ziyu; Hutter, Frank; Zoghi, Masrour; Matheson, David; de Freitas, Nando</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-JAIR-REMBO.pdf" title="pdf " target="blank">Bayesian Optimization in a Billion Dimensions via Random Embeddings</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research (JAIR), </span><span class="tp_pub_additional_volume">vol. 55, </span><span class="tp_pub_additional_pages">pp. 361-387, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_208" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('208','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{wang-jair2016,<br /> title = {Bayesian Optimization in a Billion Dimensions via Random Embeddings},<br /> author = {Ziyu Wang and Frank Hutter and Masrour Zoghi and David Matheson and Nando de Freitas},<br /> year = {2016},<br /> journal = {Journal of Artificial Intelligence Research (JAIR)},<br /> volume = {55},<br /> pages = {361-387},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_208" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-JAIR-REMBO.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fab fa-github"></i><a class="tp_pub_list" href="https://github.com/ziyuw/rembo" title="code" target="_blank">code</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('208','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Meinel, Andreas; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-BCIMeeting-HypOpt.pdf" title="pdf" target="blank">Hyperparameter Optimization for Machine Learning Problems in BCI (Abstract)</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Brain Computer Interface Meeting 2016, </span><span class="tp_pub_additional_year">2016</span>.</p><div class="tp_bibtex" id="tp_bibtex_148" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('148','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{meinel-bci16a,<br /> title = {Hyperparameter Optimization for Machine Learning Problems in BCI (Abstract)},<br /> author = {Andreas Meinel and Katharina Eggensperger and Michael Tangermann and Frank Hutter},<br /> year = {2016},<br /> booktitle = {Proceedings of the International Brain Computer Interface Meeting 2016},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_148" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-BCIMeeting-HypOpt.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('148','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Schubert, Tobias; Eggensperger, Katharina; Gkogkidis, Alexis; Hutter, Frank; Ball, Tonio; Burgard, Wolfram</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/16-ICRA-BoneParameter.pdf" title="pdf" target="blank">Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'16), </span><span class="tp_pub_additional_year">2016</span><span class="tp_pub_additional_note">, (<a href="http://aad.informatik.uni-freiburg.de/downloads/16-ICRA-BoneParameter.mp4" traget="_blank">Video</a> showing the results of the optimization procedure)</span>.</p><div class="tp_bibtex" id="tp_bibtex_179" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('179','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{schubert_icra16a,<br /> title = {Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture},<br /> author = {Tobias Schubert and Katharina Eggensperger and Alexis Gkogkidis and Frank Hutter and Tonio Ball and Wolfram Burgard},<br /> year = {2016},<br /> booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'16)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_179" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/16-ICRA-BoneParameter.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-file-video"></i><a class="tp_pub_list" href="http://aad.informatik.uni-freiburg.de/downloads/16-ICRA-BoneParameter.mp4" title="Video" target="_blank">Video</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('179','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2015">2015</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost Tobias; Blum, Manuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-NIPS-auto-sklearn-poster.pdf" title="poster " target="blank">Efficient and Robust Automated Machine Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Advances in Neural Information Processing Systems 28 (NeurIPS'15), </span><span class="tp_pub_additional_pages">pp. 2962–2970, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_54" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('54','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{feurer-neurip2015,<br /> title = {Efficient and Robust Automated Machine Learning},<br /> author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Tobias Springenberg and Manuel Blum and Frank Hutter},<br /> year = {2015},<br /> booktitle = {Advances in Neural Information Processing Systems 28 (NeurIPS'15)},<br /> pages = {2962--2970},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_54" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-NIPS-auto-sklearn-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-NIPS-auto-sklearn-supplementary.pdf" title="supplementary " target="_blank">supplementary </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-NIPS-auto-sklearn-preprint.pdf" title="preprint " target="_blank">preprint </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="https://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('54','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Klein, A; Bartels, S; Falkner, S; Hennig, P; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-BayesOpt-EnvES.pdf" title="pdf" target="blank">Towards efficient Bayesian Optimization for Big Data</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS 2015 Bayesian Optimization Workshop, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_118" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('118','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{klein-bayesopt15,<br /> title = {Towards efficient Bayesian Optimization for Big Data},<br /> author = {A Klein and S Bartels and S Falkner and P Hennig and F Hutter},<br /> year = {2015},<br /> booktitle = {NIPS 2015 Bayesian Optimization Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_118" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-BayesOpt-EnvES.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('118','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hoos, H; Hutter, F; Schaub, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-JAIR-Autofolio.pdf" title="pdf" target="blank">AutoFolio: An automatically configured Algorithm Selector</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence, </span><span class="tp_pub_additional_volume">vol. 53, </span><span class="tp_pub_additional_pages">pp. 745-778, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_132" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('132','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{lindauer-jair15a,<br /> title = {AutoFolio: An automatically configured Algorithm Selector},<br /> author = {M Lindauer and H Hoos and F Hutter and T Schaub},<br /> year = {2015},<br /> journal = {Journal of Artificial Intelligence},<br /> volume = {53},<br /> pages = {745-778},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_132" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-JAIR-Autofolio.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('132','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Falkner, S; Lindauer, M; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-SAT-SpySMAC.pdf" title="pdf" target="blank">SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Conference on Satisfiability Solving (SAT'15), </span><span class="tp_pub_additional_pages">pp. 1-8, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_41" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('41','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{falkner-sat15a,<br /> title = {SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers},<br /> author = {S Falkner and M Lindauer and F Hutter},<br /> year = {2015},<br /> booktitle = {Proceedings of the International Conference on Satisfiability Solving (SAT'15)},<br /> pages = {1-8},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_41" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-SAT-SpySMAC.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('41','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, Matthias; Klein, Aaron; Eggensperger, Katharina; Springenberg, Jost Tobias; Blum, Manuel; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-AUTOML-AutoML.pdf" title="pdf " target="blank">Methods for Improving Bayesian Optimization for AutoML</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2015 AutoML Workshop, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_47" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('47','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{feurer-automl15a,<br /> title = {Methods for Improving Bayesian Optimization for AutoML},<br /> author = {Matthias Feurer and Aaron Klein and Katharina Eggensperger and Jost Tobias Springenberg and Manuel Blum and Frank Hutter},<br /> year = {2015},<br /> booktitle = {ICML 2015 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_47" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AUTOML-AutoML.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AUTOML-AutoML-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AUTOML-AutoML-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('47','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Vallati, Mauro; Hutter, Frank; Chrpa, Lukáš; McCluskey, T L</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-IJCAI-Configuration_of_Domain_Models.pdf" title="pdf" target="blank">On the Effective Configuration of Planning Domain Models</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), </span><span class="tp_pub_additional_publisher">AAAI press, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_195" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('195','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{ValHutChrMcC15,<br /> title = {On the Effective Configuration of Planning Domain Models},<br /> author = {Mauro Vallati and Frank Hutter and Lukáš Chrpa and T L McCluskey},<br /> year = {2015},<br /> booktitle = {Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI)},<br /> publisher = {AAAI press},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_195" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-IJCAI-Configuration_of_Domain_Models.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('195','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Domhan, T; Springenberg, J T; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-IJCAI-Extrapolation_of_Learning_Curves.pdf" title="pdf" target="blank">Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_23" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('23','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{DomSprHut15,<br /> title = {Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves},<br /> author = {T Domhan and J T Springenberg and F Hutter},<br /> year = {2015},<br /> booktitle = {Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_23" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-IJCAI-Extrapolation_of_Learning_Curves.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('23','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Lücke, J; Schmidt-Thieme, L</p><p class="tp_pub_title"><a class="tp_title_link" href="http://dx.doi.org/10.1007/s13218-015-0381-0" title="publication" target="blank">Beyond Manual Tuning of Hyperparameters</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Künstliche Intelligenz, </span><span class="tp_pub_additional_volume">vol. 0, </span><span class="tp_pub_additional_pages">pp. 1-9, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_102" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('102','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{HutLueSch15,<br /> title = {Beyond Manual Tuning of Hyperparameters},<br /> author = {F Hutter and J Lücke and L Schmidt-Thieme},<br /> year = {2015},<br /> journal = {Künstliche Intelligenz},<br /> volume = {0},<br /> pages = {1-9},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_102" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://dx.doi.org/10.1007/s13218-015-0381-0" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('102','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Xu, L; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-IJCAI-JournalTrack_RuntimePrediction.pdf" title="pdf" target="blank">Algorithm runtime prediction: Methods & evaluation (extended abstract)</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_112" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('112','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutXuHooLey15,<br /> title = {Algorithm runtime prediction: Methods & evaluation (extended abstract)},<br /> author = {F Hutter and L Xu and H H Hoos and K Leyton-Brown},<br /> year = {2015},<br /> booktitle = {Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_112" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-IJCAI-JournalTrack_RuntimePrediction.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('112','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, K; Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-AAAI-Surrogates.pdf" title="pdf " target="blank">Efficient Benchmarking of Hyperparameter Optimizers via Surrogates</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_29" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('29','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Eggensperger2015,<br /> title = {Efficient Benchmarking of Hyperparameter Optimizers via Surrogates},<br /> author = {K Eggensperger and F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2015},<br /> booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_29" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-Surrogates.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-Surrogates-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('29','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, M; Springenberg, T; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-AAAI-MI-SMBO.pdf" title="pdf " target="blank">Initializing Bayesian Hyperparameter Optimization via Meta-Learning</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_55" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('55','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Feurer2015,<br /> title = {Initializing Bayesian Hyperparameter Optimization via Meta-Learning},<br /> author = {M Feurer and T Springenberg and F Hutter},<br /> year = {2015},<br /> booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_55" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-MI-SMBO.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-MI-SMBO-poster.pdf" title="poster " target="_blank">poster </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-MI-SMBO-supplementary.pdf" title="supplementary" target="_blank">supplementary</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('55','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hoos, H; Hutter, F; Schaub, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-AAAI-Autofolio.pdf" title="pdf" target="blank">AutoFolio: Algorithm Configuration for Algorithm Selection</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Ninth AAAI Workshops on Artificial Intelligence, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_123" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('123','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{lindauer-aaai15a,<br /> title = {AutoFolio: Algorithm Configuration for Algorithm Selection},<br /> author = {M Lindauer and H Hoos and F Hutter and T Schaub},<br /> year = {2015},<br /> booktitle = {Proceedings of the Twenty-Ninth AAAI Workshops on Artificial Intelligence},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_123" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-Autofolio.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('123','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Seipp, J; Sievers, S; Helmert, M; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-AAAI-Cedalion.pdf" title="pdf" target="blank">Automatic Configuration of Sequential Planning Portfolios</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_180" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('180','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Seipp2015,<br /> title = {Automatic Configuration of Sequential Planning Portfolios},<br /> author = {J Seipp and S Sievers and M Helmert and F Hutter},<br /> year = {2015},<br /> booktitle = {Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_180" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-AAAI-Cedalion.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('180','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Vanschoren, J; Bischl, B; Hutter, F; Sebag, M; Kegl, B; Schmid, M; Napolitano, G; Wolstencroft, K; Williams, A R; Lawrence, N</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-IDA-Horizon-Collaboratory.pdf" title="pdf" target="blank">Towards a Data Science Collaboratory</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Advances in Intelligent Data Analysis XIV (IDA 2015), </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_200" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('200','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{vanschoren-ida2015,<br /> title = {Towards a Data Science Collaboratory},<br /> author = {J Vanschoren and B Bischl and F Hutter and M Sebag and B Kegl and M Schmid and G Napolitano and K Wolstencroft and A R Williams and N Lawrence},<br /> year = {2015},<br /> booktitle = {Advances in Intelligent Data Analysis XIV (IDA 2015)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_200" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-IDA-Horizon-Collaboratory.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('200','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Lindauer, M; Hoos, H; F,; Hutter,</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/15-LION-ParallelAS.pdf" title="pdf" target="blank">From Sequential Algorithm Selection to Parallel Portfolio Selection</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Conference on Learning and Intelligent Optimization (LION'15), </span><span class="tp_pub_additional_year">2015</span>.</p><div class="tp_bibtex" id="tp_bibtex_134" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('134','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{lindauer-lion15a,<br /> title = {From Sequential Algorithm Selection to Parallel Portfolio Selection},<br /> author = {M Lindauer and H Hoos and F and Hutter},<br /> year = {2015},<br /> booktitle = {Proceedings of the International Conference on Learning and Intelligent Optimization (LION'15)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_134" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/15-LION-ParallelAS.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('134','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2014">2014</h3> </td> </tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Seipp, Jendrick; Sievers, Silvan; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-IPC-Fast-Downward-SMAC-Planning-and-Learning-Part.pdf" title="pdf" target="blank">Fast Downward SMAC</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2014</span><span class="tp_pub_additional_note">, (Planner abstract, <a href="http://www.cs.colostate.edu/~ipc2014/results.html" target="_blank">IPC 2014 Planning and Learning Track</a><mark>Best basic solver award</mark>, and third place in the categories overall best quality and best learner.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_182" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('182','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{SeippEtAl2014b,<br /> title = {Fast Downward SMAC},<br /> author = {Jendrick Seipp and Silvan Sievers and Frank Hutter},<br /> year = {2014},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_182" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-IPC-Fast-Downward-SMAC-Planning-and-Learning-Part.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('182','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Seipp, Jendrick; Sievers, Silvan; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-IPC-Fast-Downward-Cedalion-Planning-and-Learning-Part.pdf" title="pdf" target="blank">Fast Downward Cedalion</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2014</span><span class="tp_pub_additional_note">, (Planner abstract, <a href="http://www.cs.colostate.edu/~ipc2014/results.html" traget="_blank">IPC 2014 Planning and Learning Track</a><mark>Best learner award</mark>, and second place in the category overall best quality at the <a href="http://www.cs.colostate.edu/~ipc2014/results.html" target="_blank">IPC 2014 Planning and Learning Track</a>. Also achieved the <mark>highest coverage</mark> in the <a href="http://helios.hud.ac.uk/scommv/IPC-14/seqagi.html" target="_blank">IPC 2014 sequential agile planning track</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_181" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('181','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{SeippEtAl2014a,<br /> title = {Fast Downward Cedalion},<br /> author = {Jendrick Seipp and Silvan Sievers and Frank Hutter},<br /> year = {2014},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_181" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-IPC-Fast-Downward-Cedalion-Planning-and-Learning-Part.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('181','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-METASEL-Surrogates.pdf" title="pdf " target="blank">Surrogate Benchmarks for Hyperparameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ECAI workshop on Metalearning and Algorithm Selection (MetaSel), </span><span class="tp_pub_additional_pages">pp. 24-31, </span><span class="tp_pub_additional_year">2014</span><span class="tp_pub_additional_note">, (Superseeded by the AAAI15 paper _Efficient Benchmarking of Hyperparameter Optimizers via Surrogates_)</span>.</p><div class="tp_bibtex" id="tp_bibtex_30" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('30','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{EggHutHooLey,<br /> title = {Surrogate Benchmarks for Hyperparameter Optimization},<br /> author = {Katharina Eggensperger and Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2014},<br /> booktitle = {ECAI workshop on Metalearning and Algorithm Selection (MetaSel)},<br /> pages = {24-31},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_30" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-METASEL-Surrogates.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-METASEL-Surrogates-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('30','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Feurer, M; Springenberg, T; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-METASEL-MI-SMBO.pdf" title="pdf " target="blank">Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ECAI workshop on Metalearning and Algorithm Selection (MetaSel), </span><span class="tp_pub_additional_pages">pp. 3–10, </span><span class="tp_pub_additional_year">2014</span><span class="tp_pub_additional_note">, (Superseeded by the AAAI15 paper _Initializing Bayesian Hyperparameter Optimization via Meta-Learning_)</span>.</p><div class="tp_bibtex" id="tp_bibtex_56" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('56','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{FeuSprHut,<br /> title = {Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters},<br /> author = {M Feurer and T Springenberg and F Hutter},<br /> year = {2014},<br /> booktitle = {ECAI workshop on Metalearning and Algorithm Selection (MetaSel)},<br /> pages = {3--10},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_56" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-METASEL-MI-SMBO.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-METASEL-MI-SMBO-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('56','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Domhan, Tobias; Springenberg, Tobias; Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-AUTOML-ExtrapolatingLearningCurves4.pdf" title="pdf " target="blank">Extrapolating Learning Curves of Deep Neural Networks</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">ICML 2014 AutoML Workshop, </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_22" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('22','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{DomSprHut14,<br /> title = {Extrapolating Learning Curves of Deep Neural Networks},<br /> author = {Tobias Domhan and Tobias Springenberg and Frank Hutter},<br /> year = {2014},<br /> booktitle = {ICML 2014 AutoML Workshop},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_22" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-AUTOML-ExtrapolatingLearningCurves4.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-AUTOML-ExtrapolatingLearningCurves4-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('22','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Fawcett, Chris; Vallati, Mauro; Hutter, Frank; Hoffmann, Jörg; Hoos, Holger; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-ICAPS-Planning-Features.pdf" title="pdf" target="blank">Improved Features for Runtime Prediction of Domain-Independent Planners</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS 2014), </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_42" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('42','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{FawEtAl14:PlanningFeatures,<br /> title = {Improved Features for Runtime Prediction of Domain-Independent Planners},<br /> author = {Chris Fawcett and Mauro Vallati and Frank Hutter and Jörg Hoffmann and Holger Hoos and Kevin Leyton-Brown},<br /> year = {2014},<br /> booktitle = {Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS 2014)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_42" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-ICAPS-Planning-Features.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('42','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-ICML-HyperparameterAssessment.pdf" title="pdf " target="blank">An Efficient Approach for Assessing Hyperparameter Importance</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of International Conference on Machine Learning 2014 (ICML 2014), </span><span class="tp_pub_additional_pages">pp. 754–762, </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_95" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('95','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey14,<br /> title = {An Efficient Approach for Assessing Hyperparameter Importance},<br /> author = {F Hutter and H Hoos and K Leyton-Brown},<br /> year = {2014},<br /> booktitle = {Proceedings of International Conference on Machine Learning 2014 (ICML 2014)},<br /> pages = {754--762},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_95" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-ICML-HyperparameterAssessment.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-ICML-HyperparameterAssessment-longversion.pdf" title="longversion" target="_blank">longversion</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('95','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Leyton-Brown, Kevin; Hoos, Holger; Hutter, Frank; Xu, Lin</p><p class="tp_pub_title"><a class="tp_title_link" href="http://doi.acm.org/10.1145/2594413.2594424" title="publication " target="blank">Understanding the Empirical Hardness of NP-complete Problems</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Communications of the Association for Computing Machinery (CACM), </span><span class="tp_pub_additional_volume">vol. 57, </span><span class="tp_pub_additional_number">no. 5, </span><span class="tp_pub_additional_pages">pp. 98–107, </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_122" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('122','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{LeyHooHutXu14,<br /> title = {Understanding the Empirical Hardness of NP-complete Problems},<br /> author = {Kevin Leyton-Brown and Holger Hoos and Frank Hutter and Lin Xu},<br /> year = {2014},<br /> journal = {Communications of the Association for Computing Machinery (CACM)},<br /> volume = {57},<br /> number = {5},<br /> pages = {98--107},<br /> publisher = {ACM},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_122" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://doi.acm.org/10.1145/2594413.2594424" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-CACM-EHMs-preprint.pdf" title="preprint " target="_blank">preprint </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://dx.doi.org/10.1145/2594413.2594424" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('122','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Geschwender, Daniel; Hutter, Frank; Kotthoff, Lars; Malitsky, Yuri; Hoos, Holger; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-LION-AC_in_the_Cloud.pdf" title="pdf " target="blank">Algorithm Configuration in the Cloud: A Feasibility Study</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_69" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('69','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{GesHutKotMalHooLey14,<br /> title = {Algorithm Configuration in the Cloud: A Feasibility Study},<br /> author = {Daniel Geschwender and Frank Hutter and Lars Kotthoff and Yuri Malitsky and Holger Hoos and Kevin Leyton-Brown},<br /> year = {2014},<br /> booktitle = {Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_69" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-LION-AC_in_the_Cloud.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-LION-AC_in_the_Cloud-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('69','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; López-Ibáñez, Manuel; Fawcett, Chris; Lindauer, Marius; Hoos, Holger; Leyton-Brown, Kevin; Stützle, Thomas</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/14-LION-AClib.pdf" title="pdf " target="blank">AClib: a Benchmark Library for Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8), </span><span class="tp_pub_additional_year">2014</span>.</p><div class="tp_bibtex" id="tp_bibtex_83" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('83','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutEtAl14:AClib,<br /> title = {AClib: a Benchmark Library for Algorithm Configuration},<br /> author = {Frank Hutter and Manuel López-Ibáñez and Chris Fawcett and Marius Lindauer and Holger Hoos and Kevin Leyton-Brown and Thomas Stützle},<br /> year = {2014},<br /> booktitle = {Proceedings of the Learning and Intelligent OptimizatioN Conference (LION 8)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_83" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-LION-AClib.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/14-LION-AClib-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('83','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Xu, L; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="http://dx.doi.org/10.1016/j.artint.2013.10.003" title="publication " target="blank">Algorithm runtime prediction: Methods & evaluation</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Artificial Intelligence, </span><span class="tp_pub_additional_volume">vol. 206, </span><span class="tp_pub_additional_number">no. 0, </span><span class="tp_pub_additional_pages">pp. 79–111, </span><span class="tp_pub_additional_year">2014</span><span class="tp_pub_additional_note">, (The data and source code for this paper are available from our <a href="http://www.cs.ubc.ca/labs/beta/Projects/EPMs/" target="_blank">Empirical Performance Models project page</a>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_111" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('111','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{HutXuHooLey14,<br /> title = {Algorithm runtime prediction: Methods & evaluation},<br /> author = {F Hutter and L Xu and H H Hoos and K Leyton-Brown},<br /> year = {2014},<br /> journal = {Artificial Intelligence},<br /> volume = {206},<br /> number = {0},<br /> pages = {79--111},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_111" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="http://dx.doi.org/10.1016/j.artint.2013.10.003" title="publication " target="_blank">publication </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/1211.0906" title="arXiv" target="_blank">arXiv</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('111','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2013">2013</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-BayesOpt_fANOVA.pdf" title="pdf " target="blank">An Efficient Approach for Assessing Parameter Importance in Bayesian Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS workshop on Bayesian Optimization in Theory and Practice, </span><span class="tp_pub_additional_year">2013</span>.</p><div class="tp_bibtex" id="tp_bibtex_92" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('92','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey13,<br /> title = {An Efficient Approach for Assessing Parameter Importance in Bayesian Optimization},<br /> author = {Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2013},<br /> booktitle = {NIPS workshop on Bayesian Optimization in Theory and Practice},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_92" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-BayesOpt_fANOVA.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-BayesOpt_fANOVA-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('92','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Swersky, Kevin; Duvenaud, David; Snoek, Jasper; Hutter, Frank; Osborne, Michael</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-BayesOpt_Arc-Kernel.pdf" title="pdf" target="blank">Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS workshop on Bayesian Optimization in Theory and Practice, </span><span class="tp_pub_additional_year">2013</span>.</p><div class="tp_bibtex" id="tp_bibtex_191" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('191','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{SweDuvSnoHutOsb13,<br /> title = {Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces},<br /> author = {Kevin Swersky and David Duvenaud and Jasper Snoek and Frank Hutter and Michael Osborne},<br /> year = {2013},<br /> booktitle = {NIPS workshop on Bayesian Optimization in Theory and Practice},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_191" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-BayesOpt_Arc-Kernel.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('191','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Eggensperger, Katharina; Feurer, Matthias; Hutter, Frank; Bergstra, James; Snoek, Jasper; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-BayesOpt_EmpiricalFoundation.pdf" title="pdf " target="blank">Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NeurIPS workshop on Bayesian Optimization in Theory and Practice, </span><span class="tp_pub_additional_year">2013</span><span class="tp_pub_additional_note">, (Software and benchmarks are available from our <a href="http://www.automl.org/hpolib" target="_blank">HPOlib</a> website.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_25" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('25','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{eggensperger-bayesopt13a,<br /> title = {Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters},<br /> author = {Katharina Eggensperger and Matthias Feurer and Frank Hutter and James Bergstra and Jasper Snoek and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2013},<br /> booktitle = {NeurIPS workshop on Bayesian Optimization in Theory and Practice},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_25" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-BayesOpt_EmpiricalFoundation.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-BayesOpt_EmpiricalFoundation-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('25','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Wang, Z; Zoghi, M; Hutter, F; Matheson, D; de Freitas, N</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-IJCAI-BO-highdim.pdf" title="pdf " target="blank">Bayesian Optimization in High Dimensions via Random Embeddings</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 23rd international joint conference on Artificial Intelligence (IJCAI), </span><span class="tp_pub_additional_pages">pp. 1778-1784, </span><span class="tp_pub_additional_organization">AAAI Press </span><span class="tp_pub_additional_year">2013</span><span class="tp_pub_additional_note">, (<mark>Distinguished paper award. </mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_209" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('209','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{WangEtAl13,<br /> title = {Bayesian Optimization in High Dimensions via Random Embeddings},<br /> author = {Z Wang and M Zoghi and F Hutter and D Matheson and N de Freitas},<br /> year = {2013},<br /> booktitle = {Proceedings of the 23rd international joint conference on Artificial Intelligence (IJCAI)},<br /> pages = {1778-1784},<br /> organization = {AAAI Press},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_209" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-IJCAI-BO-highdim.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="ai ai-arxiv"></i><a class="tp_pub_list" href="http://arxiv.org/abs/1301.1942" title="arXiv " target="_blank">arXiv </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="" title="publication" target="_blank">publication</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('209','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Thornton, C; Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-KDD2013-AutoWEKA.pdf" title="pdf" target="blank">Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13), </span><span class="tp_pub_additional_year">2013</span><span class="tp_pub_additional_note">, (The software is available from our <a href="http://www.cs.ubc.ca/labs/beta/Projects/autoweka/" target="_blank">Auto-WEKA page</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_192" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('192','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{ThoHutHooLey13,<br /> title = {Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms},<br /> author = {C Thornton and F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2013},<br /> booktitle = {Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_192" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-KDD2013-AutoWEKA.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('192','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-GECCO-BBOB_SMAC.pdf" title="pdf" target="blank">An Evaluation of Sequential Model-Based Optimization for Expensive Blackbox Functions</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of GECCO-13 Workshop on Blackbox Optimization Benchmarking (BBOB'13), </span><span class="tp_pub_additional_year">2013</span><span class="tp_pub_additional_note">, (Software and data are available from the <a href="http://www.cs.ubc.ca/labs/beta/Projects/SMAC/" traget="_blank">SMAC page</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_93" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('93','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey13b,<br /> title = {An Evaluation of Sequential Model-Based Optimization for Expensive Blackbox Functions},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2013},<br /> booktitle = {Proceedings of GECCO-13 Workshop on Blackbox Optimization Benchmarking (BBOB'13)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_93" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-GECCO-BBOB_SMAC.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('93','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/13-LION-FeatureAndParameterImportance.pdf" title="pdf" target="blank">Identifying Key Algorithm Parameters and Instance Features using Forward Selection</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Nicosia, Giuseppe; Pardalos, Panos (Ed.): <span class="tp_pub_additional_booktitle">Proceedings of the 7th International Conference on Learning and Optimization (LION-7), </span><span class="tp_pub_additional_publisher">Springer Berlin Heidelberg, </span><span class="tp_pub_additional_year">2013</span><span class="tp_pub_additional_note">, (The data and source code for this paper are available from our <a href="http://www.cs.ubc.ca/labs/beta/Projects/EPMs/" traget="_blank">Empirical Performance Models project page</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_94" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('94','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{HutHooLey13c,<br /> title = {Identifying Key Algorithm Parameters and Instance Features using Forward Selection},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> editor = {Giuseppe Nicosia and Panos Pardalos},<br /> year = {2013},<br /> booktitle = {Proceedings of the 7th International Conference on Learning and Optimization (LION-7)},<br /> publisher = {Springer Berlin Heidelberg},<br /> series = {Lecture Notes in Computer Science},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_94" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/13-LION-FeatureAndParameterImportance.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('94','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2012">2012</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, Lin; Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/12-SAT-EvaluatingSolverContributions.pdf" title="pdf" target="blank">Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">International Conference on Theory and Applications of Satisfiability Testing (SAT'12), </span><span class="tp_pub_additional_year">2012</span>.</p><div class="tp_bibtex" id="tp_bibtex_219" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('219','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{XuHutHoosLey12,<br /> title = {Evaluating Component Solver Contributions to Portfolio-Based Algorithm Selectors},<br /> author = {Lin Xu and Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2012},<br /> booktitle = {International Conference on Theory and Applications of Satisfiability Testing (SAT'12)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_219" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/12-SAT-EvaluatingSolverContributions.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('219','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_unpublished"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, L; Hutter, F; Shen, J; Hoos, H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="https://helda.helsinki.fi/bitstream/handle/10138/34218/sc2012_proceedings.pdf" title="publication " target="blank">SATzilla2012: Improved Algorithm Selection Based on Cost-sensitive Classification Models</a> <span class="tp_pub_type unpublished">Unpublished</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2012</span><span class="tp_pub_additional_note">, (Published online. Solver description for the 2012 SAT challenge. <mark>SATzilla2012 won 3 out of the 4 categories</mark> for which it was eligible, and <mark>placed 2nd</mark> in the remaining one. Details: it won the sequential portfolio track, was the best solver for 2 of the 3 main sequential categories (Application and Hard Combinatorial), and 2nd in the sequential Random Category (beaten only by a new non-portfolio solver, CCASAT). See the <a href="http://www.cs.ubc.ca/labs/beta/Projects/SATzilla/" target="_blank">SATzilla</a> project page for details on SATzilla and source code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_212" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('212','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@unpublished{XuEtAl12,<br /> title = {SATzilla2012: Improved Algorithm Selection Based on Cost-sensitive Classification Models},<br /> author = {L Xu and F Hutter and J Shen and H Hoos and K Leyton-Brown},<br /> editor = {Adrian Balint and Anton Belov and Daniel Diepold and Simon Gerber and Matti Järvisalo and Carsten Sinz},<br /> year = {2012},<br /> booktitle = {Proceedings of SAT Challenge 2012: Solver and Benchmark Descriptions},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_212" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="https://helda.helsinki.fi/bitstream/handle/10138/34218/sc2012_proceedings.pdf" title="publication " target="_blank">publication </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/12-SATzilla-solver-description.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('212','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/12-LION-Parallel_AC.pdf" title="pdf " target="blank">Parallel Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Learning and Intelligent OptimizatioN Conference LION 6, </span><span class="tp_pub_additional_pages">pp. 55-70, </span><span class="tp_pub_additional_year">2012</span>.</p><div class="tp_bibtex" id="tp_bibtex_91" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('91','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey12d,<br /> title = {Parallel Algorithm Configuration},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2012},<br /> booktitle = {Proceedings of the Learning and Intelligent OptimizatioN Conference LION 6},<br /> pages = {55-70},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_91" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/12-LION-Parallel_AC.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-powerpoint"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/12-LION-Parallel_AC-slides.pptx" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('91','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2011">2011</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/11-NIPS-workshop-BO-with-censoring.pdf" title="pdf " target="blank">Bayesian Optimization With Censored Response Data</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">NIPS workshop on Bayesian Optimization, Sequential Experimental Design, and Bandits, </span><span class="tp_pub_additional_year">2011</span><span class="tp_pub_additional_note">, (Published online. There is also a new, extended <a href="http://arxiv.org/abs/1310.1947" target="_blank">arXiv</a> version.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_90" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('90','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey11b,<br /> title = {Bayesian Optimization With Censored Response Data},<br /> author = {Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2011},<br /> booktitle = {NIPS workshop on Bayesian Optimization, Sequential Experimental Design, and Bandits},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_90" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-NIPS-workshop-BO-with-censoring.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-NIPS-workshop-BO-with-censoring-poster.pdf" title="poster" target="_blank">poster</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('90','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, Lin; Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/11-IJCAI-RCRA-HydraMIP.pdf" title="pdf" target="blank">Hydra-MIP: Automated Algorithm Configuration and Selection for Mixed Integer Programming</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">RCRA workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion at the International Joint Conference on Artificial Intelligence (IJCAI), </span><span class="tp_pub_additional_year">2011</span>.</p><div class="tp_bibtex" id="tp_bibtex_214" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('214','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{XuHutHooLey,<br /> title = {Hydra-MIP: Automated Algorithm Configuration and Selection for Mixed Integer Programming},<br /> author = {Lin Xu and Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2011},<br /> booktitle = {RCRA workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion at the International Joint Conference on Artificial Intelligence (IJCAI)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_214" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-IJCAI-RCRA-HydraMIP.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('214','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, Lin; Hutter, Frank; Hoos, Holger; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/11-SATzilla.pdf" title="pdf" target="blank">Detailed SATzilla Results from the Data Analysis Track of the 2011 SAT Competition</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2011</span>.</p><div class="tp_bibtex" id="tp_bibtex_213" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('213','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{XuEtAl2011,<br /> title = {Detailed SATzilla Results from the Data Analysis Track of the 2011 SAT Competition},<br /> author = {Lin Xu and Frank Hutter and Holger Hoos and Kevin Leyton-Brown},<br /> year = {2011},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_213" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-SATzilla.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('213','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/11-LION5-SMAC.pdf" title="pdf " target="blank">Sequential Model-Based Optimization for General Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the conference on Learning and Intelligent OptimizatioN (LION 5), </span><span class="tp_pub_additional_pages">pp. 507-523, </span><span class="tp_pub_additional_year">2011</span><span class="tp_pub_additional_note">, (Best paper award (second prize). SMAC, ROAR, and the instances used are available from the <a href="http://www.cs.ubc.ca/labs/beta/Projects/AAC/index.html" target="_blank">Automated Algorithm Configuration project page</a>. An extended version with additional details is available as UBC tech report TR-2010-10. <a href="http://www.informatik.uni- freiburg.de/~aad/media/_publications/10-TR- SMAC.pdf" target="_blank">(pdf)</a> <a href="http://www.informatik.uni- freiburg.de/~aad/media/_publications/10-TR-SMAC.bib" target="_blank">(bib)</a>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_89" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('89','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey11,<br /> title = {Sequential Model-Based Optimization for General Algorithm Configuration},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2011},<br /> booktitle = {Proceedings of the conference on Learning and Intelligent OptimizatioN (LION 5)},<br /> pages = {507-523},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_89" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-LION5-SMAC.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/11-LION5-SMAC-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('89','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2010">2010</h3> </td> </tr><tr class="tp_publication tp_publication_incollection"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Bartz-Beielstein, T; Hoos, H H; Leyton-Brown, K; Murphy, K P</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/10-EMAOA-spoplus-chapter.pdf" title="pdf" target="blank">Sequential Model-Based Parameter Optimisation: an Experimental Investigation of Automated and Interactive Approaches</a> <span class="tp_pub_type incollection">Incollection</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Bartz-Beielstein, T; Chiarandini, M; Paquete, L; Preuss, M (Ed.): <span class="tp_pub_additional_booktitle">Empirical Methods for the Analysis of Optimization Algorithms, </span><span class="tp_pub_additional_pages">pp. 361–411, </span><span class="tp_pub_additional_publisher">Springer, </span><span class="tp_pub_additional_year">2010</span>.</p><div class="tp_bibtex" id="tp_bibtex_79" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('79','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@incollection{HutBeiHooLey10,<br /> title = {Sequential Model-Based Parameter Optimisation: an Experimental Investigation of Automated and Interactive Approaches},<br /> author = {F Hutter and T Bartz-Beielstein and H H Hoos and K Leyton-Brown and K P Murphy},<br /> editor = {T Bartz-Beielstein and M Chiarandini and L Paquete and M Preuss},<br /> year = {2010},<br /> booktitle = {Empirical Methods for the Analysis of Optimization Algorithms},<br /> pages = {361--411},<br /> publisher = {Springer},<br /> chapter = {15},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_79" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-EMAOA-spoplus-chapter.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('79','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/10-AMAI-SSA.pdf" title="pdf" target="blank">Tradeoffs in the Empirical Evaluation of Competing Algorithm Designs</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Annals of Mathematics and Artificial Intelligenc (AMAI), Special Issue on Learning and Intelligent Optimization, </span><span class="tp_pub_additional_volume">vol. 60, </span><span class="tp_pub_additional_number">no. 1, </span><span class="tp_pub_additional_pages">pp. 65–89, </span><span class="tp_pub_additional_year">2010</span><span class="tp_pub_additional_note">, (The data from this paper, as well as the empirical analysis tools we introduced are available from the <a href="http://www.cs.ubc.ca/labs/beta/Projects/AAC/index.html" target="_blank">Automated Algorithm Configuration</a> project page.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_86" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('86','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{HutHooLey10,<br /> title = {Tradeoffs in the Empirical Evaluation of Competing Algorithm Designs},<br /> author = {Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2010},<br /> journal = {Annals of Mathematics and Artificial Intelligenc (AMAI), Special Issue on Learning and Intelligent Optimization},<br /> volume = {60},<br /> number = {1},<br /> pages = {65--89},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_86" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-AMAI-SSA.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('86','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_techreport"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/10-TR-SMAC.pdf" title="pdf" target="blank">Sequential Model-Based Optimization for General Algorithm Configuration (extended version)</a> <span class="tp_pub_type techreport">Technical Report</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_institution">University of British Columbia, Department of Computer Science </span><span class="tp_pub_additional_number">no. TR-2010-10, </span><span class="tp_pub_additional_year">2010</span>.</p><div class="tp_bibtex" id="tp_bibtex_88" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('88','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@techreport{HutHooLey10c,<br /> title = {Sequential Model-Based Optimization for General Algorithm Configuration (extended version)},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2010},<br /> number = {TR-2010-10},<br /> institution = {University of British Columbia, Department of Computer Science},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_88" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-TR-SMAC.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('88','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/10-CPAIOR-MIP-Config.pdf" title="pdf " target="blank">Automated Configuration of Mixed Integer Programming Solvers</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CPAIOR), </span><span class="tp_pub_additional_pages">pp. 186-202, </span><span class="tp_pub_additional_year">2010</span><span class="tp_pub_additional_note">, (Our webpage on <a href="http://www.cs.ubc.ca/labs/beta/Projects/MIP-Config" target="_blank">Automated Configuration of MIP solvers</a> also gives the parameter files for CPLEX, Gurobi, and lpsolve.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_87" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('87','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLey10b,<br /> title = {Automated Configuration of Mixed Integer Programming Solvers},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2010},<br /> booktitle = {Proceedings of the Conference on Integration of Artificial Intelligence and Operations Research techniques in Constraint Programming (CPAIOR)},<br /> pages = {186-202},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_87" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-CPAIOR-MIP-Config.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-CPAIOR-MIP-Config-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('87','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K; Murphy, K P</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/10-LION-TB-SPO.pdf" title="pdf " target="blank">Time-Bounded Sequential Parameter Optimization</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the conference on Learning and Intelligent OptimizatioN (LION 4), </span><span class="tp_pub_additional_year">2010</span><span class="tp_pub_additional_note">, (<mark>Runner-up for the best paper award</mark>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_97" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('97','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLeyMur10,<br /> title = {Time-Bounded Sequential Parameter Optimization},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown and K P Murphy},<br /> year = {2010},<br /> booktitle = {Proceedings of the conference on Learning and Intelligent OptimizatioN (LION 4)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_97" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-LION-TB-SPO.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/10-LION-TB-SPO-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('97','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2009">2009</h3> </td> </tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin; Stützle, Thomas</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-JAIR-ParamILS.pdf" title="pdf" target="blank">ParamILS: An Automatic Algorithm Configuration Framework</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research, </span><span class="tp_pub_additional_volume">vol. 36, </span><span class="tp_pub_additional_pages">pp. 267–306, </span><span class="tp_pub_additional_year">2009</span><span class="tp_pub_additional_note">, (See the <a href="http://www.cs.ubc.ca/labs/beta/Projects/ParamILS" target="_blank">ParamILS project page</a> for a lot of experimental data for this paper (target algorithms, parameters, resulting parameter configurations). There's also a quick start guide available to help you apply ParamILS for tuning your own algorithms. There's also an older tech report about ParamILS, including additional material <a href="http://www.informatik.uni-freiburg.de/~aad/media/_publications/09-TR-ParamILS.pdf" target="_blank">(pdf)</a> <a href="http://www.informatik.uni-freiburg.de/~aad/media/_publications/09-TR-ParamILS.bib" target="_blank">(bib)</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_98" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('98','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{HutHooLeyStu09a,<br /> title = {ParamILS: An Automatic Algorithm Configuration Framework},<br /> author = {Frank Hutter and Holger H Hoos and Kevin Leyton-Brown and Thomas Stützle},<br /> year = {2009},<br /> journal = {Journal of Artificial Intelligence Research},<br /> volume = {36},<br /> pages = {267--306},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_98" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-JAIR-ParamILS.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('98','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_phdthesis"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-HutterPhD.pdf" title="pdf " target="blank">Automated Configuration of Algorithms for Solving Hard Computational Problems</a> <span class="tp_pub_type phdthesis">PhD Thesis</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_school">University of British Columbia, Department of Computer Science, </span><span class="tp_pub_additional_year">2009</span><span class="tp_pub_additional_note">, (There are also <a href="http://www.informatik.uni-freiburg.de/~aad/media/_publications/10-AI-PhD-in-AI.pdf" target="_blank">slides from invited presentation at Canadian AI grad student symposium</a>. <mark>2010 CAIAC Doctoral Dissertation Award</mark> for the best thesis in Artificial Intelligence at a Canadian University completed in 2009. See the <a href="http://www.cs.ubc.ca/labs/beta/Projects/AAC/" target="_blank">Automated Algorithm Configuration</a> project page for a lot of experimental data (target algorithms, parameters, benchmark instances, and configuration proceduers).)</span>.</p><div class="tp_bibtex" id="tp_bibtex_108" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('108','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@phdthesis{Hutter09,<br /> title = {Automated Configuration of Algorithms for Solving Hard Computational Problems},<br /> author = {F Hutter},<br /> year = {2009},<br /> address = {Vancouver, Canada},<br /> school = {University of British Columbia, Department of Computer Science},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_108" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-HutterPhD.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-HutterPhD-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('108','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_proceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; de Oca, M A Montes (Ed.)</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-SLS-DS-Proceedings-IridiaTR.pdf" title="pdf" target="blank">SLS-DS 2009: Doctoral Symposium on Engineering Stochastic Local Search Algorithms</a> <span class="tp_pub_type proceedings">Proceeding</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_organization">IRIDIA, Université Libre de Bruxelles, Brussels, Belgium </span><span class="tp_pub_additional_year">2009</span>.</p><div class="tp_bibtex" id="tp_bibtex_103" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('103','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@proceedings{HutOca09,<br /> title = {SLS-DS 2009: Doctoral Symposium on Engineering Stochastic Local Search Algorithms},<br /> editor = {F Hutter and M ~A Montes~de~Oca},<br /> year = {2009},<br /> organization = {IRIDIA, Université Libre de Bruxelles, Brussels, Belgium},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_103" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-SLS-DS-Proceedings-IridiaTR.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('103','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K; Murphy, K P</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-GECCO-SPO+.pdf" title="pdf " target="blank">An Experimental Investigation of Model-Based Parameter Optimisation: SPO and Beyond</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 11th annual conference on Genetic and evolutionary computation (GECCO '09), </span><span class="tp_pub_additional_pages">pp. 271–278, </span><span class="tp_pub_additional_year">2009</span>.</p><div class="tp_bibtex" id="tp_bibtex_96" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('96','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooLeyMur09,<br /> title = {An Experimental Investigation of Model-Based Parameter Optimisation: SPO and Beyond},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown and K P Murphy},<br /> year = {2009},<br /> booktitle = {Proceedings of the 11th annual conference on Genetic and evolutionary computation (GECCO '09)},<br /> pages = {271--278},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_96" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-GECCO-SPO+.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-GECCO-SPO+-presentation.pdf" title="presentation" target="_blank">presentation</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('96','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_techreport"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H H; Leyton-Brown, K; Stützle, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-TR-ParamILS.pdf" title="pdf" target="blank">ParamILS: An Automatic Algorithm Configuration Framework</a> <span class="tp_pub_type techreport">Technical Report</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_institution">University of British Columbia </span><span class="tp_pub_additional_number">no. TR-2009-01, </span><span class="tp_pub_additional_year">2009</span>.</p><div class="tp_bibtex" id="tp_bibtex_99" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('99','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@techreport{HutHooLeyStu09b,<br /> title = {ParamILS: An Automatic Algorithm Configuration Framework},<br /> author = {F Hutter and H H Hoos and K Leyton-Brown and T Stützle},<br /> year = {2009},<br /> number = {TR-2009-01},<br /> institution = {University of British Columbia},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_99" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-TR-ParamILS.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('99','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_unpublished"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, L; Hutter, F; Hoos, H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/09-SATzilla-solver-description.pdf" title="pdf" target="blank">SATzilla2009: an Automatic Algorithm Portfolio for SAT</a> <span class="tp_pub_type unpublished">Unpublished</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2009</span><span class="tp_pub_additional_note">, (Solver description, SAT competition 2009Solver description for the 2009 SAT competition. <mark>SATzilla2009 won 3 gold and 2 silver medals</mark> in that competition. See the <a href="http://www.cs.ubc.ca/labs/beta/Projects/SATzilla/" target="_blank">SATzilla project page</a> for details and source code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_218" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('218','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@unpublished{XuHutHooLey09,<br /> title = {SATzilla2009: an Automatic Algorithm Portfolio for SAT},<br /> author = {L Xu and F Hutter and H Hoos and K Leyton-Brown},<br /> year = {2009},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_218" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/09-SATzilla-solver-description.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('218','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2008">2008</h3> </td> </tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, Lin; Hutter, Frank; Hoos, Holger H; Leyton-Brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/08-JAIR-Satzilla.pdf" title="pdf" target="blank">SATzilla: Portfolio-based Algorithm Selection for SAT</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Artificial Intelligence Research, </span><span class="tp_pub_additional_volume">vol. 32, </span><span class="tp_pub_additional_pages">pp. 565–606, </span><span class="tp_pub_additional_year">2008</span><span class="tp_pub_additional_note">, (<mark>2010 IJCAI/JAIR Best Paper Prize</mark> for the period 2005-2009. See the <a href="http://www.cs.ubc.ca/labs/beta/Projects/SATzilla/" target="_blank">SATzilla project page</a> for details and source code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_217" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('217','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{XuHutHooLey08,<br /> title = {SATzilla: Portfolio-based Algorithm Selection for SAT},<br /> author = {Lin Xu and Frank Hutter and Holger H Hoos and Kevin Leyton-Brown},<br /> year = {2008},<br /> journal = {Journal of Artificial Intelligence Research},<br /> volume = {32},<br /> pages = {565--606},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_217" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/08-JAIR-Satzilla.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('217','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2007">2007</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Babic, Domagoj; Hoos, Holger H; Hu, Alan J</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-fmcad-BoostingVerification.pdf" title="pdf" target="blank">Boosting Verification by Automatic Tuning of Decision Proceedingsdures</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of Formal Methods in Computer Aided Design (FMCAD'07), </span><span class="tp_pub_additional_pages">pp. 27–34, </span><span class="tp_pub_additional_publisher">IEEE Computer Society, </span><span class="tp_pub_additional_address">Washington, DC, USA, </span><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (With the tuning discussed in this paper Domagoj's solver Spear won the QF_BV (Quantifier-Free Bit Vector) category of the <a href="http://www.smtcomp.org/" target="_blank">2007 Satisfiability Modulo Theories Competition</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_78" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('78','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutBabHooHu07,<br /> title = {Boosting Verification by Automatic Tuning of Decision Proceedingsdures},<br /> author = {Frank Hutter and Domagoj Babic and Holger H Hoos and Alan J Hu},<br /> year = {2007},<br /> booktitle = {Proceedings of Formal Methods in Computer Aided Design (FMCAD'07)},<br /> pages = {27--34},<br /> publisher = {IEEE Computer Society},<br /> address = {Washington, DC, USA},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_78" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-fmcad-BoostingVerification.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('78','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-Algorithm-configuration.pdf" title="pdf" target="blank">On the Potential of Automatic Algorithm Configuration</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Doctoral Symposium on Engineering Stochastic Local Search Algorithms (SLS-DS)., </span><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (<mark>Best poster award</mark> (voted by the attendees of SLS 07).)</span>.</p><div class="tp_bibtex" id="tp_bibtex_107" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('107','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{Hutter07,<br /> title = {On the Potential of Automatic Algorithm Configuration},<br /> author = {Frank Hutter},<br /> year = {2007},<br /> booktitle = {Proceedings of the Doctoral Symposium on Engineering Stochastic Local Search Algorithms (SLS-DS).},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_107" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-Algorithm-configuration.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('107','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, L; Hutter, F; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-CP-satzilla.pdf" title="pdf" target="blank">SATzilla-07: The Design and Analysis of an Algorithm Portfolio for SAT</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Principles and Practice of Constraint Programming (CP'07), </span><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (SATzilla won 3 gold medals, 1 silver and 1 bronze in the <a href="http://www.satcompetition.org/" target="_blank">2007 SAT competition</a>! It is available for download from the <a href="http://www.cs.ubc.ca/labs/beta/Projects/SATzilla/" target="_blank">SATzilla website</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_216" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('216','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{XuHutHooLey07b,<br /> title = {SATzilla-07: The Design and Analysis of an Algorithm Portfolio for SAT},<br /> author = {L Xu and F Hutter and H H Hoos and K Leyton-Brown},<br /> year = {2007},<br /> booktitle = {Principles and Practice of Constraint Programming (CP'07)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_216" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-CP-satzilla.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('216','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hoos, H; Stützle, T</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-AAAI_ParamILS.pdf" title="pdf " target="blank">Automatic Algorithm Configuration based on Local Search</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Twenty-Second Conference on Artifical Intelligence (AAAI '07), </span><span class="tp_pub_additional_pages">pp. 1152–1157, </span><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (The ParamILS algorithm introduced in this paper is available for download from the <a href="http://www.cs.ubc.ca/labs/beta/Projects/ParamILS" traget="_blank">ParamILS website</a>. There's also a quick start guide available to help you apply it for tuning your own algorithms.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_101" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('101','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooStu07,<br /> title = {Automatic Algorithm Configuration based on Local Search},<br /> author = {F Hutter and H Hoos and T Stützle},<br /> year = {2007},<br /> booktitle = {Proceedings of the Twenty-Second Conference on Artifical Intelligence (AAAI '07)},<br /> pages = {1152--1157},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_101" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-AAAI_ParamILS.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-AAAI_ParamILS-slides.pdf" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('101','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Tompkins, Dave; Hutter, Frank; H, Holger; Hoos,</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-satcomp-saps.pdf" title="pdf" target="blank">Scaling and Probabilistic Smoothing (SAPS)</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (SAPS is unchanged from last year, but I got a tenfold speedup by automated parameter tuning (using the techniques from the AAAI-07 ParamILS paper))</span>.</p><div class="tp_bibtex" id="tp_bibtex_194" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('194','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{TomHutHoo07,<br /> title = {Scaling and Probabilistic Smoothing (SAPS)},<br /> author = {Dave Tompkins and Frank Hutter and Holger H and Hoos},<br /> year = {2007},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_194" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-satcomp-saps.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('194','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Xu, Lin; Hutter, Frank; Hoos, Holger H; Leyton-brown, Kevin</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-SATzilla.pdf" title="pdf" target="blank">SATzilla2007: a new & improved algorithm portfolio for SAT</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (In a nutshell, SATzilla predicts the runtime of each solver in the portfolio and picks the most promising one. <mark>SATzilla2007 won 3 gold medals, 1 silver and 1 bronze!</mark> See the SAT competition webpage for details.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_215" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('215','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{XuHutHooLey07a,<br /> title = {SATzilla2007: a new & improved algorithm portfolio for SAT},<br /> author = {Lin Xu and Frank Hutter and Holger H Hoos and Kevin Leyton-brown},<br /> year = {2007},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_215" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-SATzilla.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('215','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Babić, D; Hutter, F</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/07-satcomp-spear.pdf" title="pdf" target="blank">SPEAR Theorem Prover</a> <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2007</span><span class="tp_pub_additional_note">, (Solver description, SAT competitionSPEAR is a new tree search algorithm with 25 free parameters. I tuned it (using the techniques from the AAAI-07 paper on ParamILS), getting a 30% speedup; for software verification, my parameter settings beat the default by a factor of 50!)</span>.</p><div class="tp_bibtex" id="tp_bibtex_5" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('5','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{BabHut07,<br /> title = {SPEAR Theorem Prover},<br /> author = {D Babić and F Hutter},<br /> year = {2007},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_5" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/07-satcomp-spear.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('5','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2006">2006</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Hamadi, Y; Hoos, H H; Leyton-Brown, K</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/06-CP06-autoparam.pdf" title="pdf " target="blank">Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Principles and Practice of Constraint Programming (CP'06), </span><span class="tp_pub_additional_pages">pp. 213–228, </span><span class="tp_pub_additional_year">2006</span><span class="tp_pub_additional_note">, (All our experimental data for this paper, as well as our Matlab code, is available on the <a href="http://www.cs.ubc.ca/labs/beta/Projects/Empirical-Hardness-Models/index.html" target="_blank">Empirical Hardness Models project page</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_85" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('85','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHamHooLey06b,<br /> title = {Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms},<br /> author = {F Hutter and Y Hamadi and H H Hoos and K Leyton-Brown},<br /> year = {2006},<br /> booktitle = {Principles and Practice of Constraint Programming (CP'06)},<br /> pages = {213--228},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_85" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/06-CP06-autoparam.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-powerpoint"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/06-CP06-autoparam-slides.ppt" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('85','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_misc"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank</p><p class="tp_pub_title">Automated Algorithm Configuration Based on Machine Learning <span class="tp_pub_type misc">Miscellaneous</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_year">2006</span>.</p><div class="tp_bibtex" id="tp_bibtex_106" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('106','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@misc{Hutter06,<br /> title = {Automated Algorithm Configuration Based on Machine Learning},<br /> author = {Frank Hutter},<br /> year = {2006},<br /> keywords = {}<br /> }<br /> </div></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2005">2005</h3> </td> </tr><tr class="tp_publication tp_publication_techreport"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hamadi, Youssef</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/05-msr_tr-autoparam.pdf" title="pdf" target="blank">Parameter Adjustment Based on Performance Prediction: Towards an Instance-Aware Problem Solver</a> <span class="tp_pub_type techreport">Technical Report</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_institution">Microsoft Research </span><span class="tp_pub_additional_address">Cambridge, UK, </span><span class="tp_pub_additional_number">no. MSR-TR-2005-125, </span><span class="tp_pub_additional_year">2005</span><span class="tp_pub_additional_note">, (<a href="http://www.cs.ubc.ca/~hutter/presentations/2005-4c-automated_parameter_setting.ppt" target="_blank">Slides from a talk I gave at the Cork Constraint Computation Centre (4C)</a> <a href="http://www.cs.ubc.ca/~hutter/presentations/2005-lci-automated_parameter_setting.ppt" target="_blank">Slides from a talk I gave in the Lab for Computational Intelligence at UBC</a>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_84" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('84','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@techreport{HutHam05,<br /> title = {Parameter Adjustment Based on Performance Prediction: Towards an Instance-Aware Problem Solver},<br /> author = {Frank Hutter and Youssef Hamadi},<br /> year = {2005},<br /> number = {MSR-TR-2005-125},<br /> pages = {58},<br /> address = {Cambridge, UK},<br /> institution = {Microsoft Research},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_84" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/05-msr_tr-autoparam.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('84','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Hoos, Holger H; Stützle, Thomas</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/05-ijcai-sls4mpe.pdf" title="pdf " target="blank">Efficient Stochastic Local Search for MPE Solving</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05), </span><span class="tp_pub_additional_pages">pp. 169–174, </span><span class="tp_pub_additional_year">2005</span><span class="tp_pub_additional_note">, (My solver GLS+ and the test instances we used are available on our <a href="http://www.cs.ubc.ca/labs/beta/Projects/SLS4MPE/" target="_blank">MPE page</a>. The solver can read general factor graphs, i.e. Bayes nets (in BNT format), MRFs, CRFs, etc. There's also a nice Matlab interface.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_100" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('100','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutHooStu05,<br /> title = {Efficient Stochastic Local Search for MPE Solving},<br /> author = {Frank Hutter and Holger H Hoos and Thomas Stützle},<br /> year = {2005},<br /> booktitle = {Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05)},<br /> pages = {169--174},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_100" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/05-ijcai-sls4mpe.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-powerpoint"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/05-ijcai-sls4mpe-slides.ppt" title="slides" target="_blank">slides</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('100','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2004">2004</h3> </td> </tr><tr class="tp_publication tp_publication_mastersthesis"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/04-HutterMSC.pdf" title="pdf" target="blank">Stochastic Local Search for Solving the Most Probable Explanation Problem in Bayesian Networks</a> <span class="tp_pub_type mastersthesis">Masters Thesis</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_school">Darmstadt University of Technoloy, </span><span class="tp_pub_additional_year">2004</span><span class="tp_pub_additional_note">, (Supervisor: Thomas Stützle, Cosupervisor: Holger Hoos; My solver GLS+ and most of the test instances I used are available on our <a href="http://www.cs.ubc.ca/labs/beta/Projects/SLS4MPE/" target="_blank">MPE page</a>.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_105" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('105','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@mastersthesis{Hutter04,<br /> title = {Stochastic Local Search for Solving the Most Probable Explanation Problem in Bayesian Networks},<br /> author = {Frank Hutter},<br /> year = {2004},<br /> school = {Darmstadt University of Technoloy},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_105" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-HutterMSC.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('105','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_techreport"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Ng, Brenda; Dearden, Richard</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/04-TR-AIDA.pdf" title="pdf" target="blank">Incremental Thin Junction Trees for Dynamic Bayesian Networks</a> <span class="tp_pub_type techreport">Technical Report</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_institution">Intellectics Group, Darmstadt University of Technology </span><span class="tp_pub_additional_number">no. TR-AIDA-04-01, </span><span class="tp_pub_additional_year">2004</span>.</p><div class="tp_bibtex" id="tp_bibtex_80" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('80','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@techreport{HutBreDea04,<br /> title = {Incremental Thin Junction Trees for Dynamic Bayesian Networks},<br /> author = {Frank Hutter and Brenda Ng and Richard Dearden},<br /> year = {2004},<br /> number = {TR-AIDA-04-01},<br /> institution = {Intellectics Group, Darmstadt University of Technology},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_80" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-TR-AIDA.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('80','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author">de Freitas, Nando; Dearden, Richard; Hutter, Frank; Morales-Menendez, Ruben; Mutch, Jim; Poole, David</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/04-IEEE.pdf" title="pdf " target="blank">Diagnosis by a Waiter and a Mars Explorer</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Proceedings of the IEEE, </span><span class="tp_pub_additional_volume">vol. 92, </span><span class="tp_pub_additional_number">no. 4, </span><span class="tp_pub_additional_pages">pp. 139-144, </span><span class="tp_pub_additional_year">2004</span><span class="tp_pub_additional_note">, (Check out my <a href="http://www.cs.ubc.ca/~hutter/research/gpf/gpf.html" target="_blank">GPF webpage</a> for the particle filtering code used for the rover examples.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_61" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('61','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{FreEtAl04,<br /> title = {Diagnosis by a Waiter and a Mars Explorer},<br /> author = {Nando de Freitas and Richard Dearden and Frank Hutter and Ruben Morales-Menendez and Jim Mutch and David Poole},<br /> year = {2004},<br /> journal = {Proceedings of the IEEE},<br /> volume = {92},<br /> number = {4},<br /> pages = {139-144},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_61" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-IEEE.pdf" title="pdf " target="_blank">pdf </a></li><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-IEEE-Aerospace.pdf" title="Aerospace " target="_blank">Aerospace </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-IEEE-Aerospace.bib" title="Aerospace " target="_blank">Aerospace </a></li><li><i class="fas fa-globe"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-IEEE-Aerospace.yaml" title="Aerospace" target="_blank">Aerospace</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('61','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Dearden, Richard; Willeke, Thomas; Hutter, Frank; Simmons, Reid; Verma, Vandi; Thrun, Sebastian</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/04-IEEE-Aerospace.pdf" title="pdf" target="blank">Real-time Fault Detection and Situational Awareness for Rovers: Report on the Mars Technology Program Task</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">In Proceedings of IEEE Aerospace Conference, 2004, </span><span class="tp_pub_additional_pages">pp. 826–840, </span><span class="tp_pub_additional_publisher">IEEE Press, </span><span class="tp_pub_additional_year">2004</span><span class="tp_pub_additional_note">, (Check out my <a href="http://www.cs.ubc.ca/~hutter/research/gpf/gpf.html" target="_blank">GPF webpage</a> for the particle filtering code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_21" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('21','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{DeaEtAl04,<br /> title = {Real-time Fault Detection and Situational Awareness for Rovers: Report on the Mars Technology Program Task},<br /> author = {Richard Dearden and Thomas Willeke and Frank Hutter and Reid Simmons and Vandi Verma and Sebastian Thrun},<br /> year = {2004},<br /> booktitle = {In Proceedings of IEEE Aerospace Conference, 2004},<br /> pages = {826--840},<br /> publisher = {IEEE Press},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_21" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-IEEE-Aerospace.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('21','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_article"><td class="tp_pub_info"><p class="tp_pub_author"> Andronescu, M; Fejes, A P; Hutter, F; Hoos, H H; Condon, A</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/04-JMB.pdf" title="pdf" target="blank">A new algorithm for RNA secondary structure design</a> <span class="tp_pub_type article">Journal Article</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_journal">Journal of Molecular Biology, </span><span class="tp_pub_additional_volume">vol. 336, </span><span class="tp_pub_additional_number">no. 3, </span><span class="tp_pub_additional_pages">pp. 607–624, </span><span class="tp_pub_additional_year">2004</span><span class="tp_pub_additional_note">, (Check out the free RNA Designer Software at <http://www.rnasoft.ca/>)</span>.</p><div class="tp_bibtex" id="tp_bibtex_44" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('44','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@article{FejEtAl04,<br /> title = {A new algorithm for RNA secondary structure design},<br /> author = {M Andronescu and A P Fejes and F Hutter and H H Hoos and A Condon},<br /> year = {2004},<br /> journal = {Journal of Molecular Biology},<br /> volume = {336},<br /> number = {3},<br /> pages = {607--624},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_44" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/04-JMB.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('44','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2003">2003</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Dearden, Richard</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/03-DX-GPF.pdf" title="pdf" target="blank">The Gaussian Particle Filter for Diagnosis of Non-Linear Systems</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Proceedings of the 14th International Conference on Principles of Diagnosis(DX03), </span><span class="tp_pub_additional_pages">pp. 5–70, </span><span class="tp_pub_additional_year">2003</span><span class="tp_pub_additional_note">, (Check out my <a href="http://www.cs.ubc.ca/~hutter/research/gpf/gpf.html" target="_blank">GPF</a> webpage for the Gaussian particle filtering code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_81" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('81','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutDea03a,<br /> title = {The Gaussian Particle Filter for Diagnosis of Non-Linear Systems},<br /> author = {Frank Hutter and Richard Dearden},<br /> year = {2003},<br /> booktitle = {Proceedings of the 14th International Conference on Principles of Diagnosis(DX03)},<br /> pages = {5--70},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_81" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/03-DX-GPF.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('81','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, Frank; Dearden, Richard</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/03-DX-GPF_2.pdf" title="pdf" target="blank">Efficient On-line Fault Diagnosis for Non-Linear Systems</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span><span class="tp_pub_additional_booktitle">Seventh International Symposium on Artificial Intelligence and Robotics in Space (i-SAIRAS-03), </span><span class="tp_pub_additional_year">2003</span><span class="tp_pub_additional_note">, (Check out my <a href="http://www.cs.ubc.ca/~hutter/research/gpf/gpf.html" target="_blank">GPF</a> webpage for the Gaussian particle filtering code.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_82" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('82','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutDea03b,<br /> title = {Efficient On-line Fault Diagnosis for Non-Linear Systems},<br /> author = {Frank Hutter and Richard Dearden},<br /> year = {2003},<br /> booktitle = {Seventh International Symposium on Artificial Intelligence and Robotics in Space (i-SAIRAS-03)},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_82" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/03-DX-GPF_2.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('82','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr> <td> <h3 class="tp_h3" id="tp_h3_2002">2002</h3> </td> </tr><tr class="tp_publication tp_publication_inproceedings"><td class="tp_pub_info"><p class="tp_pub_author"> Hutter, F; Tompkins, D A D; Hoos, H H</p><p class="tp_pub_title"><a class="tp_title_link" href="/wp-content/uploads/papers/02-CP-saps.pdf" title="pdf" target="blank">Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT</a> <span class="tp_pub_type inproceedings">Inproceedings</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_in">In: </span> Hentenryck, Pascal (Ed.): <span class="tp_pub_additional_booktitle">Principles and Practice of Constraint Programming - CP 2002, </span><span class="tp_pub_additional_pages">pp. 233-248, </span><span class="tp_pub_additional_publisher">Springer Berlin Heidelberg, </span><span class="tp_pub_additional_year">2002</span><span class="tp_pub_additional_note">, (Check out the <a href="http://www.cs.ubc.ca/~davet/dls4sat/" target="_blank">DLS for SAT</a> webpage, maintained by Dave.)</span>.</p><div class="tp_bibtex" id="tp_bibtex_110" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('110','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@inproceedings{HutTomHoo02,<br /> title = {Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT},<br /> author = {F Hutter and D A D Tompkins and H H Hoos},<br /> editor = {Pascal Hentenryck},<br /> year = {2002},<br /> booktitle = {Principles and Practice of Constraint Programming - CP 2002},<br /> volume = {2470},<br /> pages = {233-248},<br /> publisher = {Springer Berlin Heidelberg},<br /> series = {Lecture Notes in Computer Science},<br /> keywords = {}<br /> }<br /> </div></div></div><div class="tp_links" id="tp_links_110" attMe="" ><div class="tp_links_entry"><ul class="tp_pub_list"><li><i class="fas fa-file-pdf"></i><a class="tp_pub_list" href="/wp-content/uploads/papers/02-CP-saps.pdf" title="pdf" target="_blank">pdf</a></li><li><i class="fas fa-quote-right"></i><a class="tp_close" onclick="teachpress_pub_showhide('110','tp_bibtex')">bibtex</a></li></ul></div></div></td></tr><tr class="tp_publication tp_publication_techreport"><td class="tp_pub_info"><p class="tp_pub_author"> Andronescu, M; Fejes, A P; Hutter, F; Hoos, H H; Condon, A</p><p class="tp_pub_title">A New SLS Algorithm for RNA Secondary Structure Design <span class="tp_pub_type techreport">Technical Report</span> </p><p class="tp_pub_additional"><span class="tp_pub_additional_institution">Department of Computer Science, University of British Columbia </span><span class="tp_pub_additional_number">no. TR-2002-10, </span><span class="tp_pub_additional_year">2002</span><span class="tp_pub_additional_note">, (Available as a <a href="http://www.informatik.uni-freiburg.de/~aad/media/_publications/02-TECHREPORT-SLS-ALGORITHM.ps.tar.gz" target="_blank">postscript file</a>. Check out the free RNA Designer Software at http://www.rnasoft.ca/)</span>.</p><div class="tp_bibtex" id="tp_bibtex_43" attMe="" style="display:none;" ><div><p class="tp_close_menu"><a class="tp_close" onclick="teachpress_pub_showhide('43','tp_bibtex')"><i class="fas fa-times-circle"></i></a></p><div class="tp_bibtex_entry">@techreport{FejEtAl02,<br /> title = {A New SLS Algorithm for RNA Secondary Structure Design},<br /> author = {M Andronescu and A P Fejes and F Hutter and H H Hoos and A Condon},<br /> year = {2002},<br /> number = {TR-2002-10},<br /> institution = {Department of Computer Science, University of British Columbia},<br /> keywords = {}<br /> }<br /> </div></div></div></td></tr></table></div></div></div></div> <p></p> </div> </article> </main> </div> </div> <footer id="colophon" class="site-footer"> <div class="site-info"> <div class="upper-footer"> <nav class="social-navigation" aria-label="Social Links Menu"> <div class="menu-social-container"><ul id="menu-social" 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