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Machine Learning May 2022
<!DOCTYPE html> <html lang="en"> <head> <title>Machine Learning May 2022</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <link rel="apple-touch-icon" sizes="180x180" href="/static/browse/0.3.4/images/icons/apple-touch-icon.png"> <link rel="icon" type="image/png" sizes="32x32" href="/static/browse/0.3.4/images/icons/favicon-32x32.png"> <link rel="icon" type="image/png" sizes="16x16" href="/static/browse/0.3.4/images/icons/favicon-16x16.png"> <link rel="manifest" href="/static/browse/0.3.4/images/icons/site.webmanifest"> <link rel="mask-icon" href="/static/browse/0.3.4/images/icons/safari-pinned-tab.svg" color="#5bbad5"> <meta name="msapplication-TileColor" content="#da532c"> <meta name="theme-color" content="#ffffff"> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/arXiv.css?v=20241206" /> <link rel="stylesheet" type="text/css" media="print" href="/static/browse/0.3.4/css/arXiv-print.css?v=20200611" /> <link 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class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/2022-05?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2022-05?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2022-05?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/2205.00047" title="Abstract" id="2205.00047"> arXiv:2205.00047 </a> [<a href="/pdf/2205.00047" title="Download PDF" id="pdf-2205.00047" aria-labelledby="pdf-2205.00047">pdf</a>, <a href="/format/2205.00047" title="Other formats" id="oth-2205.00047" aria-labelledby="oth-2205.00047">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Logically Consistent Adversarial Attacks for Soft Theorem Provers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Gaskell,+A">Alexander Gaskell</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Miao,+Y">Yishu Miao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Specia,+L">Lucia Specia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Toni,+F">Francesca Toni</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> IJCAI-ECAI 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL); Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2205.00072" title="Abstract" id="2205.00072"> arXiv:2205.00072 </a> [<a href="/pdf/2205.00072" title="Download PDF" id="pdf-2205.00072" aria-labelledby="pdf-2205.00072">pdf</a>, <a href="/format/2205.00072" title="Other formats" id="oth-2205.00072" aria-labelledby="oth-2205.00072">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Doubting AI Predictions: Influence-Driven Second Opinion Recommendation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=De-Arteaga,+M">Maria De-Arteaga</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chouldechova,+A">Alexandra Chouldechova</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dubrawski,+A">Artur Dubrawski</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ACM CHI 2022 Workshop on Trust and Reliance in AI-Human Teams (TRAIT) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computers and Society (cs.CY); Human-Computer Interaction (cs.HC) </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2205.00107" title="Abstract" id="2205.00107"> arXiv:2205.00107 </a> [<a href="/pdf/2205.00107" title="Download PDF" id="pdf-2205.00107" aria-labelledby="pdf-2205.00107">pdf</a>, <a href="/format/2205.00107" title="Other formats" id="oth-2205.00107" aria-labelledby="oth-2205.00107">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+H">Heng Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ling,+Q">Qing Ling</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> IJCAI-ECAI 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2205.00129" title="Abstract" id="2205.00129"> arXiv:2205.00129 </a> [<a href="/pdf/2205.00129" title="Download PDF" id="pdf-2205.00129" aria-labelledby="pdf-2205.00129">pdf</a>, <a href="/format/2205.00129" title="Other formats" id="oth-2205.00129" aria-labelledby="oth-2205.00129">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Gaze-enhanced Crossmodal Embeddings for Emotion Recognition </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Abdou,+A">Ahmed Abdou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sood,+E">Ekta Sood</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=M%C3%BCller,+P">Philipp M眉ller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bulling,+A">Andreas Bulling</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2205.00142" title="Abstract" id="2205.00142"> arXiv:2205.00142 </a> [<a href="/pdf/2205.00142" title="Download PDF" id="pdf-2205.00142" aria-labelledby="pdf-2205.00142">pdf</a>, <a href="/format/2205.00142" title="Other formats" id="oth-2205.00142" aria-labelledby="oth-2205.00142">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multimodal Representation Learning With Text and Images </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jayagopal,+A">Aishwarya Jayagopal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Aiswarya,+A+M">Ankireddy Monica Aiswarya</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Garg,+A">Ankita Garg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nandakumar,+S+K">Srinivasan Kolumam Nandakumar</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2205.00147" title="Abstract" id="2205.00147"> arXiv:2205.00147 </a> [<a href="/pdf/2205.00147" title="Download PDF" id="pdf-2205.00147" aria-labelledby="pdf-2205.00147">pdf</a>, <a href="https://arxiv.org/html/2205.00147v5" title="View HTML" id="html-2205.00147" aria-labelledby="html-2205.00147" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2205.00147" title="Other formats" id="oth-2205.00147" aria-labelledby="oth-2205.00147">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DIRA: Dynamic Domain Incremental Regularised Adaptation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ghobrial,+A">Abanoub Ghobrial</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+X">Xuan Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hond,+D">Darryl Hond</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Asgari,+H">Hamid Asgari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Eder,+K">Kerstin Eder</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2205.00163" title="Abstract" id="2205.00163"> arXiv:2205.00163 </a> [<a href="/pdf/2205.00163" title="Download PDF" id="pdf-2205.00163" aria-labelledby="pdf-2205.00163">pdf</a>, <a href="/format/2205.00163" title="Other formats" id="oth-2205.00163" aria-labelledby="oth-2205.00163">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep Ensemble as a Gaussian Process Approximate Posterior </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+Z">Zhijie Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+F">Feng Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J">Jianfei Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+G">Guoqiang Wu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+J">Jun Zhu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2205.00165" title="Abstract" id="2205.00165"> arXiv:2205.00165 </a> [<a href="/pdf/2205.00165" title="Download PDF" id="pdf-2205.00165" aria-labelledby="pdf-2205.00165">pdf</a>, <a href="/format/2205.00165" title="Other formats" id="oth-2205.00165" aria-labelledby="oth-2205.00165">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> NeuralEF: Deconstructing Kernels by Deep Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+Z">Zhijie Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shi,+J">Jiaxin Shi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+J">Jun Zhu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> International Conference on Machine Learning (ICML), 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2205.00172" title="Abstract" id="2205.00172"> arXiv:2205.00172 </a> [<a href="/pdf/2205.00172" title="Download PDF" id="pdf-2205.00172" aria-labelledby="pdf-2205.00172">pdf</a>, <a href="/format/2205.00172" title="Other formats" id="oth-2205.00172" aria-labelledby="oth-2205.00172">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shang,+X">Xinyi Shang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+Y">Yang Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cheung,+Y">Yiu-ming Cheung</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+H">Hanzi Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by ICME 2022, camera-ready version </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2205.00222" title="Abstract" id="2205.00222"> arXiv:2205.00222 </a> [<a href="/pdf/2205.00222" title="Download PDF" id="pdf-2205.00222" aria-labelledby="pdf-2205.00222">pdf</a>, <a href="/format/2205.00222" title="Other formats" id="oth-2205.00222" aria-labelledby="oth-2205.00222">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> StorSeismic: A new paradigm in deep learning for seismic processing </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Harsuko,+R">Randy Harsuko</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Alkhalifah,+T">Tariq Alkhalifah</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 18 pages, 18 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP); Computational Physics (physics.comp-ph); Geophysics (physics.geo-ph) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2205.00224" title="Abstract" id="2205.00224"> arXiv:2205.00224 </a> [<a href="/pdf/2205.00224" title="Download PDF" id="pdf-2205.00224" aria-labelledby="pdf-2205.00224">pdf</a>, <a href="/format/2205.00224" title="Other formats" id="oth-2205.00224" aria-labelledby="oth-2205.00224">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Loss Function Entropy Regularization for Diverse Decision Boundaries </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chong,+S+S">Sue Sin Chong</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 7 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 2022 7th International Conference on Big Data Analytics (ICBDA) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2205.00242" title="Abstract" id="2205.00242"> arXiv:2205.00242 </a> [<a href="/pdf/2205.00242" title="Download PDF" id="pdf-2205.00242" aria-labelledby="pdf-2205.00242">pdf</a>, <a href="/format/2205.00242" title="Other formats" id="oth-2205.00242" aria-labelledby="oth-2205.00242">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Approximating Permutations with Neural Network Components for Travelling Photographer Problem </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chong,+S+S">Sue Sin Chong</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Published in 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML 2022) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2205.00256" title="Abstract" id="2205.00256"> arXiv:2205.00256 </a> [<a href="/pdf/2205.00256" title="Download PDF" id="pdf-2205.00256" aria-labelledby="pdf-2205.00256">pdf</a>, <a href="/format/2205.00256" title="Other formats" id="oth-2205.00256" aria-labelledby="oth-2205.00256">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Huo,+C">Cuiying Huo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+D">Dongxiao He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yawen Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jin,+D">Di Jin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dang,+J">Jianwu Dang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+W">Weixiong Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pedrycz,+W">Witold Pedrycz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+L">Lingfei Wu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2205.00263" title="Abstract" id="2205.00263"> arXiv:2205.00263 </a> [<a href="/pdf/2205.00263" title="Download PDF" id="pdf-2205.00263" aria-labelledby="pdf-2205.00263">pdf</a>, <a href="/format/2205.00263" title="Other formats" id="oth-2205.00263" aria-labelledby="oth-2205.00263">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ferrari,+C">Claudio Ferrari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Muller,+M+N">Mark Niklas Muller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jovanovic,+N">Nikola Jovanovic</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vechev,+M">Martin Vechev</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Software Engineering (cs.SE) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2205.00281" title="Abstract" id="2205.00281"> arXiv:2205.00281 </a> [<a href="/pdf/2205.00281" title="Download PDF" id="pdf-2205.00281" aria-labelledby="pdf-2205.00281">pdf</a>, <a href="/format/2205.00281" title="Other formats" id="oth-2205.00281" aria-labelledby="oth-2205.00281">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Understanding the Generalization Performance of Spectral Clustering Algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+S">Shaojie Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ouyang,+S">Sheng Ouyang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yong Liu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2205.00293" title="Abstract" id="2205.00293"> arXiv:2205.00293 </a> [<a href="/pdf/2205.00293" title="Download PDF" id="pdf-2205.00293" aria-labelledby="pdf-2205.00293">pdf</a>, <a href="/format/2205.00293" title="Other formats" id="oth-2205.00293" aria-labelledby="oth-2205.00293">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sozykin,+K">Konstantin Sozykin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chertkov,+A">Andrei Chertkov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schutski,+R">Roman Schutski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Phan,+A">Anh-Huy Phan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cichocki,+A">Andrzej Cichocki</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Oseledets,+I">Ivan Oseledets</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26 pages, 8 figures, accepted to Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022). Pre camera-ready version </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Neural and Evolutionary Computing (cs.NE); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2205.00302" title="Abstract" id="2205.00302"> arXiv:2205.00302 </a> [<a href="/pdf/2205.00302" title="Download PDF" id="pdf-2205.00302" aria-labelledby="pdf-2205.00302">pdf</a>, <a href="/format/2205.00302" title="Other formats" id="oth-2205.00302" aria-labelledby="oth-2205.00302">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+P">Pengbo Hu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+X">Xingyu Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Y">Yi Zhou</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> submitted to IJCAI2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2205.00329" title="Abstract" id="2205.00329"> arXiv:2205.00329 </a> [<a href="/pdf/2205.00329" title="Download PDF" id="pdf-2205.00329" aria-labelledby="pdf-2205.00329">pdf</a>, <a href="/format/2205.00329" title="Other formats" id="oth-2205.00329" aria-labelledby="oth-2205.00329">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Continual Learning with Foundation Models: An Empirical Study of Latent Replay </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ostapenko,+O">Oleksiy Ostapenko</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lesort,+T">Timothee Lesort</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rodr%C3%ADguez,+P">Pau Rodr铆guez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Arefin,+M+R">Md Rifat Arefin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Douillard,+A">Arthur Douillard</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rish,+I">Irina Rish</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Charlin,+L">Laurent Charlin</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2205.00334" title="Abstract" id="2205.00334"> arXiv:2205.00334 </a> [<a href="/pdf/2205.00334" title="Download PDF" id="pdf-2205.00334" aria-labelledby="pdf-2205.00334">pdf</a>, <a href="/format/2205.00334" title="Other formats" id="oth-2205.00334" aria-labelledby="oth-2205.00334">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Engineering flexible machine learning systems by traversing functionally-invariant paths </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Raghavan,+G">Guruprasad Raghavan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tharwat,+B">Bahey Tharwat</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hari,+S+N">Surya Narayanan Hari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Satani,+D">Dhruvil Satani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thomson,+M">Matt Thomson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Differential Geometry (math.DG) </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/2205.00354" title="Abstract" id="2205.00354"> arXiv:2205.00354 </a> [<a href="/pdf/2205.00354" title="Download PDF" id="pdf-2205.00354" aria-labelledby="pdf-2205.00354">pdf</a>, <a href="/format/2205.00354" title="Other formats" id="oth-2205.00354" aria-labelledby="oth-2205.00354">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Graph Anisotropic Diffusion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Elhag,+A+A+A">Ahmed A. A. Elhag</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Corso,+G">Gabriele Corso</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=St%C3%A4rk,+H">Hannes St盲rk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bronstein,+M+M">Michael M. Bronstein</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 pages, 3 figures, Published at the GTRL and MLDD workshops, ICLR 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/2205.00359" title="Abstract" id="2205.00359"> arXiv:2205.00359 </a> [<a href="/pdf/2205.00359" title="Download PDF" id="pdf-2205.00359" aria-labelledby="pdf-2205.00359">pdf</a>, <a href="/format/2205.00359" title="Other formats" id="oth-2205.00359" aria-labelledby="oth-2205.00359">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Brophy,+J">Jonathan Brophy</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hammoudeh,+Z">Zayd Hammoudeh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lowd,+D">Daniel Lowd</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 47 pages, 15 figures, and 5 tables. Accepted to JMLR </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2205.00361" title="Abstract" id="2205.00361"> arXiv:2205.00361 </a> [<a href="/pdf/2205.00361" title="Download PDF" id="pdf-2205.00361" aria-labelledby="pdf-2205.00361">pdf</a>, <a href="/format/2205.00361" title="Other formats" id="oth-2205.00361" aria-labelledby="oth-2205.00361">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Combined Learning of Neural Network Weights for Privacy in Collaborative Tasks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ioste,+A+R">Aline R. Ioste</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Durham,+A+M">Alan M. Durham</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Finger,+M">Marcelo Finger</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2205.00403" title="Abstract" id="2205.00403"> arXiv:2205.00403 </a> [<a href="/pdf/2205.00403" title="Download PDF" id="pdf-2205.00403" aria-labelledby="pdf-2205.00403">pdf</a>, <a href="/format/2205.00403" title="Other formats" id="oth-2205.00403" aria-labelledby="oth-2205.00403">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+J+Z">Jeremiah Zhe Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Padhy,+S">Shreyas Padhy</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+J">Jie Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lin,+Z">Zi Lin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wen,+Y">Yeming Wen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jerfel,+G">Ghassen Jerfel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nado,+Z">Zack Nado</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Snoek,+J">Jasper Snoek</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tran,+D">Dustin Tran</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lakshminarayanan,+B">Balaji Lakshminarayanan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> arXiv admin note: text overlap with <a href="https://arxiv.org/abs/2006.10108" data-arxiv-id="2006.10108" class="link-https">arXiv:2006.10108</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2205.00420" title="Abstract" id="2205.00420"> arXiv:2205.00420 </a> [<a href="/pdf/2205.00420" title="Download PDF" id="pdf-2205.00420" aria-labelledby="pdf-2205.00420">pdf</a>, <a href="/format/2205.00420" title="Other formats" id="oth-2205.00420" aria-labelledby="oth-2205.00420">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Uniform Manifold Approximation with Two-phase Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jeon,+H">Hyeon Jeon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ko,+H">Hyung-Kwon Ko</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+S">Soohyun Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jo,+J">Jaemin Jo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Seo,+J">Jinwook Seo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> IEEE VIS 2022. Hyeon Jeon and Hyung-Kwon Ko equally contributed to this work </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2205.00427" title="Abstract" id="2205.00427"> arXiv:2205.00427 </a> [<a href="/pdf/2205.00427" title="Download PDF" id="pdf-2205.00427" aria-labelledby="pdf-2205.00427">pdf</a>, <a href="/format/2205.00427" title="Other formats" id="oth-2205.00427" aria-labelledby="oth-2205.00427">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resources </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xing,+D">Dong Xing</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+Q">Qian Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Q">Qianhui Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pan,+G">Gang Pan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by IJCAI 2022 (Long Oral) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/2205.00436" title="Abstract" id="2205.00436"> arXiv:2205.00436 </a> [<a href="/pdf/2205.00436" title="Download PDF" id="pdf-2205.00436" aria-labelledby="pdf-2205.00436">pdf</a>, <a href="/format/2205.00436" title="Other formats" id="oth-2205.00436" aria-labelledby="oth-2205.00436">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation? </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Arcolezi,+H+H">H茅ber H. Arcolezi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Couchot,+J">Jean-Fran莽ois Couchot</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Renaud,+D">Denis Renaud</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bouna,+B+A">Bechara Al Bouna</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiao,+X">Xiaokui Xiao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Final version accepted in the journal Neural Computing and Applications </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/2205.00470" title="Abstract" id="2205.00470"> arXiv:2205.00470 </a> [<a href="/pdf/2205.00470" title="Download PDF" id="pdf-2205.00470" aria-labelledby="pdf-2205.00470">pdf</a>, <a href="/format/2205.00470" title="Other formats" id="oth-2205.00470" aria-labelledby="oth-2205.00470">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reward Systems for Trustworthy Medical Federated Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Pandl,+K+D">Konstantin D. Pandl</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Leiser,+F">Florian Leiser</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thiebes,+S">Scott Thiebes</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sunyaev,+A">Ali Sunyaev</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computers and Society (cs.CY); Computer Science and Game Theory (cs.GT) </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/2205.00473" title="Abstract" id="2205.00473"> arXiv:2205.00473 </a> [<a href="/pdf/2205.00473" title="Download PDF" id="pdf-2205.00473" aria-labelledby="pdf-2205.00473">pdf</a>, <a href="/format/2205.00473" title="Other formats" id="oth-2205.00473" aria-labelledby="oth-2205.00473">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Survey on Distributed Online Optimization and Game </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+X">Xiuxian Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xie,+L">Lihua Xie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+N">Na Li</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2205.00477" title="Abstract" id="2205.00477"> arXiv:2205.00477 </a> [<a href="/pdf/2205.00477" title="Download PDF" id="pdf-2205.00477" aria-labelledby="pdf-2205.00477">pdf</a>, <a href="/format/2205.00477" title="Other formats" id="oth-2205.00477" aria-labelledby="oth-2205.00477">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Ridgeless Regression with Random Features </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jian Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yong Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yingying Zhang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at IJCAI 2022 </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI). 2022: 3208-3214 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Theory (cs.IT); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2205.00487" title="Abstract" id="2205.00487"> arXiv:2205.00487 </a> [<a href="/pdf/2205.00487" title="Download PDF" id="pdf-2205.00487" aria-labelledby="pdf-2205.00487">pdf</a>, <a href="/format/2205.00487" title="Other formats" id="oth-2205.00487" aria-labelledby="oth-2205.00487">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the speed of uniform convergence in Mercer's theorem </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Takhanov,+R">Rustem Takhanov</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Spectral Theory (math.SP) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/2205.00511" title="Abstract" id="2205.00511"> arXiv:2205.00511 </a> [<a href="/pdf/2205.00511" title="Download PDF" id="pdf-2205.00511" aria-labelledby="pdf-2205.00511">pdf</a>, <a href="/format/2205.00511" title="Other formats" id="oth-2205.00511" aria-labelledby="oth-2205.00511">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Early Fault Detection Method of Rotating Machines Based on Multiple Feature Fusion with Stacking Architecture </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+W">Wenbin Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+D">Di Wu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shen,+W">Weiming Shen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Boulet,+B">Benoit Boulet</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> The results require to be updated </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/2205.00517" title="Abstract" id="2205.00517"> arXiv:2205.00517 </a> [<a href="/pdf/2205.00517" title="Download PDF" id="pdf-2205.00517" aria-labelledby="pdf-2205.00517">pdf</a>, <a href="/format/2205.00517" title="Other formats" id="oth-2205.00517" aria-labelledby="oth-2205.00517">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Accurate non-stationary short-term traffic flow prediction method </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+W">Wenzheng Zhao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 7 figures, 2 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Robotics (cs.RO) </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2205.00525" title="Abstract" id="2205.00525"> arXiv:2205.00525 </a> [<a href="/pdf/2205.00525" title="Download PDF" id="pdf-2205.00525" aria-labelledby="pdf-2205.00525">pdf</a>, <a href="/format/2205.00525" title="Other formats" id="oth-2205.00525" aria-labelledby="oth-2205.00525">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep vs. Shallow Learning: A Benchmark Study in Low Magnitude Earthquake Detection </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Goel,+A">Akshat Goel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gorse,+D">Denise Gorse</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computer Vision and Pattern Recognition (cs.CV); Geophysics (physics.geo-ph) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/2205.00534" title="Abstract" id="2205.00534"> arXiv:2205.00534 </a> [<a href="/pdf/2205.00534" title="Download PDF" id="pdf-2205.00534" aria-labelledby="pdf-2205.00534">pdf</a>, <a href="/format/2205.00534" title="Other formats" id="oth-2205.00534" aria-labelledby="oth-2205.00534">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generalized Reference Kernel for One-class Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Raitoharju,+J">Jenni Raitoharju</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Iosifidis,+A">Alexandros Iosifidis</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> International Joint Conference on Neural Networks (IJCNN), 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2205.00538" title="Abstract" id="2205.00538"> arXiv:2205.00538 </a> [<a href="/pdf/2205.00538" title="Download PDF" id="pdf-2205.00538" aria-labelledby="pdf-2205.00538">pdf</a>, <a href="/format/2205.00538" title="Other formats" id="oth-2205.00538" aria-labelledby="oth-2205.00538">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Can Information Behaviour Inform Machine Learning? </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ridley,+M">Michael Ridley</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 19 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Human-Computer Interaction (cs.HC) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2205.00550" title="Abstract" id="2205.00550"> arXiv:2205.00550 </a> [<a href="/pdf/2205.00550" title="Download PDF" id="pdf-2205.00550" aria-labelledby="pdf-2205.00550">pdf</a>, <a href="/format/2205.00550" title="Other formats" id="oth-2205.00550" aria-labelledby="oth-2205.00550">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bano,+S">Saira Bano</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Machumilane,+A">Achilles Machumilane</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Valerio,+L">Lorenzo Valerio</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cassar%C3%A0,+P">Pietro Cassar脿</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gotta,+A">Alberto Gotta</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Networking and Internet Architecture (cs.NI) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2205.00579" title="Abstract" id="2205.00579"> arXiv:2205.00579 </a> [<a href="/pdf/2205.00579" title="Download PDF" id="pdf-2205.00579" aria-labelledby="pdf-2205.00579">pdf</a>, <a href="/format/2205.00579" title="Other formats" id="oth-2205.00579" aria-labelledby="oth-2205.00579">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zeng,+K">Kevin Zeng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Linot,+A+J">Alec J. Linot</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Graham,+M+D">Michael D. Graham</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Chaotic Dynamics (nlin.CD) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2205.00618" title="Abstract" id="2205.00618"> arXiv:2205.00618 </a> [<a href="/pdf/2205.00618" title="Download PDF" id="pdf-2205.00618" aria-labelledby="pdf-2205.00618">pdf</a>, <a href="/format/2205.00618" title="Other formats" id="oth-2205.00618" aria-labelledby="oth-2205.00618">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> LoopStack: a Lightweight Tensor Algebra Compiler Stack </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wasti,+B">Bram Wasti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cambronero,+J+P">Jos茅 Pablo Cambronero</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Steiner,+B">Benoit Steiner</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Leather,+H">Hugh Leather</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zlateski,+A">Aleksandar Zlateski</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Performance (cs.PF); Symbolic Computation (cs.SC) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2205.00664" title="Abstract" id="2205.00664"> arXiv:2205.00664 </a> [<a href="/pdf/2205.00664" title="Download PDF" id="pdf-2205.00664" aria-labelledby="pdf-2205.00664">pdf</a>, <a href="/format/2205.00664" title="Other formats" id="oth-2205.00664" aria-labelledby="oth-2205.00664">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study) </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Weiss,+M">Michael Weiss</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tonella,+P">Paolo Tonella</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at ISSTA 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Software Engineering (cs.SE) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/2205.00690" title="Abstract" id="2205.00690"> arXiv:2205.00690 </a> [<a href="/pdf/2205.00690" title="Download PDF" id="pdf-2205.00690" aria-labelledby="pdf-2205.00690">pdf</a>, <a href="/format/2205.00690" title="Other formats" id="oth-2205.00690" aria-labelledby="oth-2205.00690">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bae,+H">HeeSun Bae</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shin,+S">Seungjae Shin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Na,+B">Byeonghu Na</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jang,+J">JoonHo Jang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+K">Kyungwoo Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moon,+I">Il-Chul Moon</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 21 pages, 9 figures. International Conference on Machine Learning (ICML 2022), Baltimore, Jul 17, 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/2205.00706" title="Abstract" id="2205.00706"> arXiv:2205.00706 </a> [<a href="/pdf/2205.00706" title="Download PDF" id="pdf-2205.00706" aria-labelledby="pdf-2205.00706">pdf</a>, <a href="/format/2205.00706" title="Other formats" id="oth-2205.00706" aria-labelledby="oth-2205.00706">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FedDKD: Federated Learning with Decentralized Knowledge Distillation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+X">Xinjia Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+B">Boyu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+W">Wenlian Lu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 7 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2205.00741" title="Abstract" id="2205.00741"> arXiv:2205.00741 </a> [<a href="/pdf/2205.00741" title="Download PDF" id="pdf-2205.00741" aria-labelledby="pdf-2205.00741">pdf</a>, <a href="/format/2205.00741" title="Other formats" id="oth-2205.00741" aria-labelledby="oth-2205.00741">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+L">Lijun Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+W">Wei Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yi,+J">Jinfeng Yi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+T">Tianbao Yang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2205.00756" title="Abstract" id="2205.00756"> arXiv:2205.00756 </a> [<a href="/pdf/2205.00756" title="Download PDF" id="pdf-2205.00756" aria-labelledby="pdf-2205.00756">pdf</a>, <a href="/format/2205.00756" title="Other formats" id="oth-2205.00756" aria-labelledby="oth-2205.00756">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> VICE: Variational Interpretable Concept Embeddings </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Muttenthaler,+L">Lukas Muttenthaler</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+C+Y">Charles Y. Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=McClure,+P">Patrick McClure</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vandermeulen,+R+A">Robert A. Vandermeulen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hebart,+M+N">Martin N. Hebart</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pereira,+F">Francisco Pereira</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at NeurIPS 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Applications (stat.AP); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/2205.00772" title="Abstract" id="2205.00772"> arXiv:2205.00772 </a> [<a href="/pdf/2205.00772" title="Download PDF" id="pdf-2205.00772" aria-labelledby="pdf-2205.00772">pdf</a>, <a href="/format/2205.00772" title="Other formats" id="oth-2205.00772" aria-labelledby="oth-2205.00772">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large Neighborhood Search based on Neural Construction Heuristics </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Falkner,+J+K">Jonas K. Falkner</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thyssens,+D">Daniela Thyssens</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schmidt-Thieme,+L">Lars Schmidt-Thieme</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/2205.00807" title="Abstract" id="2205.00807"> arXiv:2205.00807 </a> [<a href="/pdf/2205.00807" title="Download PDF" id="pdf-2205.00807" aria-labelledby="pdf-2205.00807">pdf</a>, <a href="/format/2205.00807" title="Other formats" id="oth-2205.00807" aria-labelledby="oth-2205.00807">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep-Attack over the Deep Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yang Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pan,+Q">Quan Pan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cambria,+E">Erik Cambria</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted to Knowledge-Based Systems </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR); Computers and Society (cs.CY) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/2205.00824" title="Abstract" id="2205.00824"> arXiv:2205.00824 </a> [<a href="/pdf/2205.00824" title="Download PDF" id="pdf-2205.00824" aria-labelledby="pdf-2205.00824">pdf</a>, <a href="/format/2205.00824" title="Other formats" id="oth-2205.00824" aria-labelledby="oth-2205.00824">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exploration in Deep Reinforcement Learning: A Survey </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ladosz,+P">Pawel Ladosz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Weng,+L">Lilian Weng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+M">Minwoo Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Oh,+H">Hyondong Oh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/2205.00832" title="Abstract" id="2205.00832"> arXiv:2205.00832 </a> [<a href="/pdf/2205.00832" title="Download PDF" id="pdf-2205.00832" aria-labelledby="pdf-2205.00832">pdf</a>, <a href="https://arxiv.org/html/2205.00832v2" title="View HTML" id="html-2205.00832" aria-labelledby="html-2205.00832" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2205.00832" title="Other formats" id="oth-2205.00832" aria-labelledby="oth-2205.00832">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Gradient Descent, Stochastic Optimization, and Other Tales </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+J">Jun Lu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Neural and Evolutionary Computing (cs.NE); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/2205.00904" title="Abstract" id="2205.00904"> arXiv:2205.00904 </a> [<a href="/pdf/2205.00904" title="Download PDF" id="pdf-2205.00904" aria-labelledby="pdf-2205.00904">pdf</a>, <a href="/format/2205.00904" title="Other formats" id="oth-2205.00904" aria-labelledby="oth-2205.00904">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tang,+Z">Zhenwei Tang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pei,+S">Shichao Pei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Z">Zhao Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+Y">Yongchun Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhuang,+F">Fuzhen Zhuang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hoehndorf,+R">Robert Hoehndorf</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+X">Xiangliang Zhang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> IJCAI 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2205.00905" title="Abstract" id="2205.00905"> arXiv:2205.00905 </a> [<a href="/pdf/2205.00905" title="Download PDF" id="pdf-2205.00905" aria-labelledby="pdf-2205.00905">pdf</a>, <a href="/format/2205.00905" title="Other formats" id="oth-2205.00905" aria-labelledby="oth-2205.00905">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yuansheng Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+W">Wangbin Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+K">Kun Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+Z">Zulun Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+L">Liang Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+Z">Zibin Zheng</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/2205.00920" title="Abstract" id="2205.00920"> arXiv:2205.00920 </a> [<a href="/pdf/2205.00920" title="Download PDF" id="pdf-2205.00920" aria-labelledby="pdf-2205.00920">pdf</a>, <a href="/format/2205.00920" title="Other formats" id="oth-2205.00920" aria-labelledby="oth-2205.00920">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Revisiting Gaussian Neurons for Online Clustering with Unknown Number of Clusters </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Eidheim,+O+C">Ole Christian Eidheim</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Reviewed at <a href="https://openreview.net/forum?id=h05RLBNweX&referrer=%5BTMLR%5D(%2Fgroup%3Fid%3DTMLR)" rel="external noopener nofollow" class="link-external link-https">this https URL</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computer Vision and Pattern Recognition (cs.CV); Neural and Evolutionary Computing (cs.NE) </div> </div> </dd> </dl> <div class='paging'>Total of 2724 entries : <span>1-50</span> <a href=/list/cs.LG/2022-05?skip=50&show=50>51-100</a> <a href=/list/cs.LG/2022-05?skip=100&show=50>101-150</a> <a href=/list/cs.LG/2022-05?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/2022-05?skip=2700&show=50>2701-2724</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/2022-05?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2022-05?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2022-05?skip=0&show=2000 rel="nofollow"> all</a> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em"> <!-- Macro-Column 1 --> <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; 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