Machine Learning Dec 2023

<!DOCTYPE html> <html lang="en"> <head> <title>Machine Learning Dec 2023</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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<a href=/list/cs.LG/2023-12?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2023-12?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2023-12?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/2312.00003" title="Abstract" id="2312.00003"> arXiv:2312.00003 </a> [<a href="/pdf/2312.00003" title="Download PDF" id="pdf-2312.00003" aria-labelledby="pdf-2312.00003">pdf</a>, <a href="/format/2312.00003" title="Other formats" id="oth-2312.00003" aria-labelledby="oth-2312.00003">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Transport Equation based Physics Informed Neural Network to predict the Yield Strength of Architected Materials </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mishra,+A">Akshansh Mishra</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computational Engineering, Finance, and Science (cs.CE); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2312.00066" title="Abstract" id="2312.00066"> arXiv:2312.00066 </a> [<a href="/pdf/2312.00066" title="Download PDF" id="pdf-2312.00066" aria-labelledby="pdf-2312.00066">pdf</a>, <a href="/format/2312.00066" title="Other formats" id="oth-2312.00066" aria-labelledby="oth-2312.00066">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Rafe,+A">Amir Rafe</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Singleton,+P+A">Patrick A. Singleton</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='item3'>[3]</a> <a href ="/abs/2312.00076" title="Abstract" id="2312.00076"> arXiv:2312.00076 </a> [<a href="/pdf/2312.00076" title="Download PDF" id="pdf-2312.00076" aria-labelledby="pdf-2312.00076">pdf</a>, <a href="/format/2312.00076" title="Other formats" id="oth-2312.00076" aria-labelledby="oth-2312.00076">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Towards A Foundation Model For Trajectory Intelligence </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Najjar,+A">Alameen Najjar</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted to the 2023 IEEE International Conference on Data Mining Workshops (ICDMW) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computers and Society (cs.CY); Social and Information Networks (cs.SI) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2312.00088" title="Abstract" id="2312.00088"> arXiv:2312.00088 </a> [<a href="/pdf/2312.00088" title="Download PDF" id="pdf-2312.00088" aria-labelledby="pdf-2312.00088">pdf</a>, <a href="/format/2312.00088" title="Other formats" id="oth-2312.00088" aria-labelledby="oth-2312.00088">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Anomaly Detection via Learning-Based Sequential Controlled Sensing </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Joseph,+G">Geethu Joseph</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhong,+C">Chen Zhong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gursoy,+M+C">M. Cenk Gursoy</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Velipasalar,+S">Senem Velipasalar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Varshney,+P+K">Pramod K. Varshney</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP); Systems and Control (eess.SY) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2312.00090" title="Abstract" id="2312.00090"> arXiv:2312.00090 </a> [<a href="/pdf/2312.00090" title="Download PDF" id="pdf-2312.00090" aria-labelledby="pdf-2312.00090">pdf</a>, <a href="/format/2312.00090" title="Other formats" id="oth-2312.00090" aria-labelledby="oth-2312.00090">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological Features </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Berlanger,+N">Nick Berlanger</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=van+Ophoven,+N">Noah van Ophoven</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Verdonck,+T">Tim Verdonck</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wilms,+I">Ines Wilms</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2312.00095" title="Abstract" id="2312.00095"> arXiv:2312.00095 </a> [<a href="/pdf/2312.00095" title="Download PDF" id="pdf-2312.00095" aria-labelledby="pdf-2312.00095">pdf</a>, <a href="/format/2312.00095" title="Other formats" id="oth-2312.00095" aria-labelledby="oth-2312.00095">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Textual-Knowledge-Guided Numerical Feature Discovery Method for Power Demand Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ning,+Z">Zifan Ning</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jin,+M">Min Jin</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 12 figures </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/2312.00102" title="Abstract" id="2312.00102"> arXiv:2312.00102 </a> [<a href="/pdf/2312.00102" title="Download PDF" id="pdf-2312.00102" aria-labelledby="pdf-2312.00102">pdf</a>, <a href="https://arxiv.org/html/2312.00102v4" title="View HTML" id="html-2312.00102" aria-labelledby="html-2312.00102" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00102" title="Other formats" id="oth-2312.00102" aria-labelledby="oth-2312.00102">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Meng,+F">Fanfei Meng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+L">Lele Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yuxin Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Miss some important information and references. The publication hasn't been online in the journal </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings on Engineering Sciences, 2620-2832, 2023/10 </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='item8'>[8]</a> <a href ="/abs/2312.00103" title="Abstract" id="2312.00103"> arXiv:2312.00103 </a> [<a href="/pdf/2312.00103" title="Download PDF" id="pdf-2312.00103" aria-labelledby="pdf-2312.00103">pdf</a>, <a href="/format/2312.00103" title="Other formats" id="oth-2312.00103" aria-labelledby="oth-2312.00103">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DeepEn2023: Energy Datasets for Edge Artificial Intelligence </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tu,+X">Xiaolong Tu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mallik,+A">Anik Mallik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+H">Haoxin Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xie,+J">Jiang Xie</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> arXiv admin note: text overlap with <a href="https://arxiv.org/abs/2310.18329" data-arxiv-id="2310.18329" class="link-https">arXiv:2310.18329</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Performance (cs.PF) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2312.00111" title="Abstract" id="2312.00111"> arXiv:2312.00111 </a> [<a href="/pdf/2312.00111" title="Download PDF" id="pdf-2312.00111" aria-labelledby="pdf-2312.00111">pdf</a>, <a href="https://arxiv.org/html/2312.00111v4" title="View HTML" id="html-2312.00111" aria-labelledby="html-2312.00111" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00111" title="Other formats" id="oth-2312.00111" aria-labelledby="oth-2312.00111">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multimodal Foundation Models for Material Property Prediction and Discovery </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Moro,+V">Viggo Moro</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Loh,+C">Charlotte Loh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dangovski,+R">Rumen Dangovski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ghorashi,+A">Ali Ghorashi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+A">Andrew Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Z">Zhuo Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+S">Samuel Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+P+Y">Peter Y. Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Christensen,+T">Thomas Christensen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Solja%C4%8Di%C4%87,+M">Marin Solja膷i膰</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 4 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Newton, Volume 1, Issue 1, 100016 (2025) Newton, Volume 1, Issue 1, 100016 (2025) Newton, Volume 1, Issue 1, 100016 (2025) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Materials Science (cond-mat.mtrl-sci) </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2312.00157" title="Abstract" id="2312.00157"> arXiv:2312.00157 </a> [<a href="/pdf/2312.00157" title="Download PDF" id="pdf-2312.00157" aria-labelledby="pdf-2312.00157">pdf</a>, <a href="https://arxiv.org/html/2312.00157v2" title="View HTML" id="html-2312.00157" aria-labelledby="html-2312.00157" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00157" title="Other formats" id="oth-2312.00157" aria-labelledby="oth-2312.00157">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Universal Backdoor Attacks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Schneider,+B">Benjamin Schneider</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lukas,+N">Nils Lukas</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kerschbaum,+F">Florian Kerschbaum</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for publication at ICLR 2024 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2312.00170" title="Abstract" id="2312.00170"> arXiv:2312.00170 </a> [<a href="/pdf/2312.00170" title="Download PDF" id="pdf-2312.00170" aria-labelledby="pdf-2312.00170">pdf</a>, <a href="https://arxiv.org/html/2312.00170v2" title="View HTML" id="html-2312.00170" aria-labelledby="html-2312.00170" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00170" title="Other formats" id="oth-2312.00170" aria-labelledby="oth-2312.00170">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> When Is Inductive Inference Possible? </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+Z">Zhou Lu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Neurips 2024, spotlight </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/2312.00189" title="Abstract" id="2312.00189"> arXiv:2312.00189 </a> [<a href="/pdf/2312.00189" title="Download PDF" id="pdf-2312.00189" aria-labelledby="pdf-2312.00189">pdf</a>, <a href="/format/2312.00189" title="Other formats" id="oth-2312.00189" aria-labelledby="oth-2312.00189">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HeTriNet: Heterogeneous Graph Triplet Attention Network for Drug-Target-Disease Interaction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tanvir,+F">Farhan Tanvir</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saifuddin,+K+M">Khaled Mohammed Saifuddin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hossain,+T">Tanvir Hossain</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bagavathi,+A">Arunkumar Bagavathi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Akbas,+E">Esra Akbas</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 13 pages, 3 figures, 6 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Biomolecules (q-bio.BM) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2312.00192" title="Abstract" id="2312.00192"> arXiv:2312.00192 </a> [<a href="/pdf/2312.00192" title="Download PDF" id="pdf-2312.00192" aria-labelledby="pdf-2312.00192">pdf</a>, <a href="/format/2312.00192" title="Other formats" id="oth-2312.00192" aria-labelledby="oth-2312.00192">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Benchmarking and Enhancing Disentanglement in Concept-Residual Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zabounidis,+R">Renos Zabounidis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Oguntola,+I">Ini Oguntola</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+K">Konghao Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Campbell,+J">Joseph Campbell</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stepputtis,+S">Simon Stepputtis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sycara,+K">Katia Sycara</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='item14'>[14]</a> <a href ="/abs/2312.00194" title="Abstract" id="2312.00194"> arXiv:2312.00194 </a> [<a href="/pdf/2312.00194" title="Download PDF" id="pdf-2312.00194" aria-labelledby="pdf-2312.00194">pdf</a>, <a href="/format/2312.00194" title="Other formats" id="oth-2312.00194" aria-labelledby="oth-2312.00194">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robust Concept Erasure via Kernelized Rate-Distortion Maximization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chowdhury,+S+B+R">Somnath Basu Roy Chowdhury</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Monath,+N">Nicholas Monath</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dubey,+A">Avinava Dubey</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ahmed,+A">Amr Ahmed</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chaturvedi,+S">Snigdha Chaturvedi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NeurIPS 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2312.00198" title="Abstract" id="2312.00198"> arXiv:2312.00198 </a> [<a href="/pdf/2312.00198" title="Download PDF" id="pdf-2312.00198" aria-labelledby="pdf-2312.00198">pdf</a>, <a href="https://arxiv.org/html/2312.00198v2" title="View HTML" id="html-2312.00198" aria-labelledby="html-2312.00198" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00198" title="Other formats" id="oth-2312.00198" aria-labelledby="oth-2312.00198">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Attack and Defense for Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=McMahan,+J">Jeremy McMahan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+Y">Young Wu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+X">Xiaojin Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xie,+Q">Qiaomin Xie</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of the AAAI Conference on Artificial Intelligence, 38(13), 14332-14340. 2024 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR); Computer Science and Game Theory (cs.GT) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2312.00209" title="Abstract" id="2312.00209"> arXiv:2312.00209 </a> [<a href="/pdf/2312.00209" title="Download PDF" id="pdf-2312.00209" aria-labelledby="pdf-2312.00209">pdf</a>, <a href="/format/2312.00209" title="Other formats" id="oth-2312.00209" aria-labelledby="oth-2312.00209">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Interplay Between Stepsize Tuning and Progressive Sharpening </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Roulet,+V">Vincent Roulet</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Agarwala,+A">Atish Agarwala</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pedregosa,+F">Fabian Pedregosa</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Presented at the NeurIPS 2023 OPT Wokshop </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2312.00232" title="Abstract" id="2312.00232"> arXiv:2312.00232 </a> [<a href="/pdf/2312.00232" title="Download PDF" id="pdf-2312.00232" aria-labelledby="pdf-2312.00232">pdf</a>, <a href="/format/2312.00232" title="Other formats" id="oth-2312.00232" aria-labelledby="oth-2312.00232">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=M%C3%B6llers,+A">Alexander M枚llers</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Immer,+A">Alexander Immer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Isufi,+E">Elvin Isufi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fortuin,+V">Vincent Fortuin</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2312.00234" title="Abstract" id="2312.00234"> arXiv:2312.00234 </a> [<a href="/pdf/2312.00234" title="Download PDF" id="pdf-2312.00234" aria-labelledby="pdf-2312.00234">pdf</a>, <a href="/format/2312.00234" title="Other formats" id="oth-2312.00234" aria-labelledby="oth-2312.00234">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep Equilibrium Based Neural Operators for Steady-State PDEs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Marwah,+T">Tanya Marwah</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pokle,+A">Ashwini Pokle</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kolter,+J+Z">J. Zico Kolter</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lipton,+Z+C">Zachary C. Lipton</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+J">Jianfeng Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Risteski,+A">Andrej Risteski</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NeurIPS 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Numerical Analysis (math.NA); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2312.00237" title="Abstract" id="2312.00237"> arXiv:2312.00237 </a> [<a href="/pdf/2312.00237" title="Download PDF" id="pdf-2312.00237" aria-labelledby="pdf-2312.00237">pdf</a>, <a href="/format/2312.00237" title="Other formats" id="oth-2312.00237" aria-labelledby="oth-2312.00237">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Negotiated Representations to Prevent Forgetting in Machine Learning Applications </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Korhan,+N">Nuri Korhan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=%C3%96ner,+C">Ceren 脰ner</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 19 pages, 9 figures, 1 table. arXiv admin note: text overlap with <a href="https://arxiv.org/abs/2010.15277" data-arxiv-id="2010.15277" class="link-https">arXiv:2010.15277</a>, <a href="https://arxiv.org/abs/2102.09517" data-arxiv-id="2102.09517" class="link-https">arXiv:2102.09517</a>, <a href="https://arxiv.org/abs/2201.00766" data-arxiv-id="2201.00766" class="link-https">arXiv:2201.00766</a> by other authors </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='item20'>[20]</a> <a href ="/abs/2312.00246" title="Abstract" id="2312.00246"> arXiv:2312.00246 </a> [<a href="/pdf/2312.00246" title="Download PDF" id="pdf-2312.00246" aria-labelledby="pdf-2312.00246">pdf</a>, <a href="https://arxiv.org/html/2312.00246v4" title="View HTML" id="html-2312.00246" aria-labelledby="html-2312.00246" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00246" title="Other formats" id="oth-2312.00246" aria-labelledby="oth-2312.00246">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Directions of Curvature as an Explanation for Loss of Plasticity </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lewandowski,+A">Alex Lewandowski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tanaka,+H">Haruto Tanaka</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schuurmans,+D">Dale Schuurmans</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Machado,+M+C">Marlos C. Machado</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='item21'>[21]</a> <a href ="/abs/2312.00267" title="Abstract" id="2312.00267"> arXiv:2312.00267 </a> [<a href="/pdf/2312.00267" title="Download PDF" id="pdf-2312.00267" aria-labelledby="pdf-2312.00267">pdf</a>, <a href="https://arxiv.org/html/2312.00267v3" title="View HTML" id="html-2312.00267" aria-labelledby="html-2312.00267" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00267" title="Other formats" id="oth-2312.00267" aria-labelledby="oth-2312.00267">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sample Efficient Preference Alignment in LLMs via Active Exploration </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mehta,+V">Viraj Mehta</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Belakaria,+S">Syrine Belakaria</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Das,+V">Vikramjeet Das</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Neopane,+O">Ojash Neopane</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dai,+Y">Yijia Dai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bogunovic,+I">Ilija Bogunovic</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Engelhardt,+B">Barbara Engelhardt</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ermon,+S">Stefano Ermon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schneider,+J">Jeff Schneider</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Neiswanger,+W">Willie Neiswanger</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2312.00268" title="Abstract" id="2312.00268"> arXiv:2312.00268 </a> [<a href="/pdf/2312.00268" title="Download PDF" id="pdf-2312.00268" aria-labelledby="pdf-2312.00268">pdf</a>, <a href="/format/2312.00268" title="Other formats" id="oth-2312.00268" aria-labelledby="oth-2312.00268">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Academic competitions </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Escalante,+H+J">Hugo Jair Escalante</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kruchinina,+A">Aleksandra Kruchinina</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='item23'>[23]</a> <a href ="/abs/2312.00271" title="Abstract" id="2312.00271"> arXiv:2312.00271 </a> [<a href="/pdf/2312.00271" title="Download PDF" id="pdf-2312.00271" aria-labelledby="pdf-2312.00271">pdf</a>, <a href="https://arxiv.org/html/2312.00271v3" title="View HTML" id="html-2312.00271" aria-labelledby="html-2312.00271" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00271" title="Other formats" id="oth-2312.00271" aria-labelledby="oth-2312.00271">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Towards Clinical Prediction with Transparency: An Explainable AI Approach to Survival Modelling in Residential Aged Care </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Susnjak,+T">Teo Susnjak</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Griffin,+E">Elise Griffin</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='item24'>[24]</a> <a href ="/abs/2312.00276" title="Abstract" id="2312.00276"> arXiv:2312.00276 </a> [<a href="/pdf/2312.00276" title="Download PDF" id="pdf-2312.00276" aria-labelledby="pdf-2312.00276">pdf</a>, <a href="https://arxiv.org/html/2312.00276v3" title="View HTML" id="html-2312.00276" aria-labelledby="html-2312.00276" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00276" title="Other formats" id="oth-2312.00276" aria-labelledby="oth-2312.00276">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Metalearning Continual Learning Algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Irie,+K">Kazuki Irie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Csord%C3%A1s,+R">R贸bert Csord谩s</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schmidhuber,+J">J眉rgen Schmidhuber</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted to TMLR 02/2025. An earlier version of this work titled "Automating Continual Learning" was made available online in 2023 </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/2312.00277" title="Abstract" id="2312.00277"> arXiv:2312.00277 </a> [<a href="/pdf/2312.00277" title="Download PDF" id="pdf-2312.00277" aria-labelledby="pdf-2312.00277">pdf</a>, <a href="/format/2312.00277" title="Other formats" id="oth-2312.00277" aria-labelledby="oth-2312.00277">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Text Attribute Control via Closed-Loop Disentanglement </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sha,+L">Lei Sha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lukasiewicz,+T">Thomas Lukasiewicz</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> accepted by TACL 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/2312.00279" title="Abstract" id="2312.00279"> arXiv:2312.00279 </a> [<a href="/pdf/2312.00279" title="Download PDF" id="pdf-2312.00279" aria-labelledby="pdf-2312.00279">pdf</a>, <a href="https://arxiv.org/html/2312.00279v2" title="View HTML" id="html-2312.00279" aria-labelledby="html-2312.00279" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00279" title="Other formats" id="oth-2312.00279" aria-labelledby="oth-2312.00279">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=He,+X">Xingqiu He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=You,+C">Chaoqun You</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Quek,+T+Q+S">Tony Q. S. Quek</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='item27'>[27]</a> <a href ="/abs/2312.00290" title="Abstract" id="2312.00290"> arXiv:2312.00290 </a> [<a href="/pdf/2312.00290" title="Download PDF" id="pdf-2312.00290" aria-labelledby="pdf-2312.00290">pdf</a>, <a href="/format/2312.00290" title="Other formats" id="oth-2312.00290" aria-labelledby="oth-2312.00290">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning to forecast diagnostic parameters using pre-trained weather embedding </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mitra,+P+P">Peetak P. Mitra</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ramavajjala,+V">Vivek Ramavajjala</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted as a spotlight paper at the NeurIPS 2023 workshop on Tackling Climate Change with Machine Learning </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='item28'>[28]</a> <a href ="/abs/2312.00296" title="Abstract" id="2312.00296"> arXiv:2312.00296 </a> [<a href="/pdf/2312.00296" title="Download PDF" id="pdf-2312.00296" aria-labelledby="pdf-2312.00296">pdf</a>, <a href="https://arxiv.org/html/2312.00296v2" title="View HTML" id="html-2312.00296" aria-labelledby="html-2312.00296" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00296" title="Other formats" id="oth-2312.00296" aria-labelledby="oth-2312.00296">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Cheng,+B">Biqian Cheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Papalexakis,+E+E">Evangelos E. Papalexakis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J">Jia Chen</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 4 pages, 7 figures, KDD SoCal symposium 2023 (extended version) </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='item29'>[29]</a> <a href ="/abs/2312.00304" title="Abstract" id="2312.00304"> arXiv:2312.00304 </a> [<a href="/pdf/2312.00304" title="Download PDF" id="pdf-2312.00304" aria-labelledby="pdf-2312.00304">pdf</a>, <a href="/format/2312.00304" title="Other formats" id="oth-2312.00304" aria-labelledby="oth-2312.00304">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Developmental Pretraining (DPT) for Image Classification Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Rajesh,+N">Niranjan Rajesh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gupta,+D">Debayan Gupta</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 7 pages, 4 figures </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='item30'>[30]</a> <a href ="/abs/2312.00336" title="Abstract" id="2312.00336"> arXiv:2312.00336 </a> [<a href="/pdf/2312.00336" title="Download PDF" id="pdf-2312.00336" aria-labelledby="pdf-2312.00336">pdf</a>, <a href="/format/2312.00336" title="Other formats" id="oth-2312.00336" aria-labelledby="oth-2312.00336">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Hypergraph Node Representation Learning with One-Stage Message Passing </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Qu,+S">Shilin Qu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+W">Weiqing Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yuan-Fang Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+X">Xin Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yuan,+F">Fajie Yuan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Retrieval (cs.IR) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/2312.00342" title="Abstract" id="2312.00342"> arXiv:2312.00342 </a> [<a href="/pdf/2312.00342" title="Download PDF" id="pdf-2312.00342" aria-labelledby="pdf-2312.00342">pdf</a>, <a href="/format/2312.00342" title="Other formats" id="oth-2312.00342" aria-labelledby="oth-2312.00342">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value at Risk </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+D">Dohyeong Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Oh,+S">Songhwai Oh</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> RA-L and IROS 2022 </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7644-7651, July 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='item32'>[32]</a> <a href ="/abs/2312.00359" title="Abstract" id="2312.00359"> arXiv:2312.00359 </a> [<a href="/pdf/2312.00359" title="Download PDF" id="pdf-2312.00359" aria-labelledby="pdf-2312.00359">pdf</a>, <a href="/format/2312.00359" title="Other formats" id="oth-2312.00359" aria-labelledby="oth-2312.00359">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Y">Yefan Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pang,+T">Tianyu Pang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+K">Keqin Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Martin,+C+H">Charles H. Martin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mahoney,+M+W">Michael W. Mahoney</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yaoqing Yang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NeurIPS 2023 Spotlight, first two authors contributed equally </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='item33'>[33]</a> <a href ="/abs/2312.00364" title="Abstract" id="2312.00364"> arXiv:2312.00364 </a> [<a href="/pdf/2312.00364" title="Download PDF" id="pdf-2312.00364" aria-labelledby="pdf-2312.00364">pdf</a>, <a href="https://arxiv.org/html/2312.00364v1" title="View HTML" id="html-2312.00364" aria-labelledby="html-2312.00364" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00364" title="Other formats" id="oth-2312.00364" aria-labelledby="oth-2312.00364">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Benchmarking Multi-Domain Active Learning on Image Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jiayi Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Taori,+R">Rohan Taori</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hashimoto,+T+B">Tatsunori B. Hashimoto</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='item34'>[34]</a> <a href ="/abs/2312.00373" title="Abstract" id="2312.00373"> arXiv:2312.00373 </a> [<a href="/pdf/2312.00373" title="Download PDF" id="pdf-2312.00373" aria-labelledby="pdf-2312.00373">pdf</a>, <a href="/format/2312.00373" title="Other formats" id="oth-2312.00373" aria-labelledby="oth-2312.00373">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Streaming Bayesian Modeling for predicting Fat-Tailed Customer Lifetime Value </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Calabourdin,+A+V">Alexey V. Calabourdin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Aksenov,+K+A">Konstantin A. Aksenov</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Work in progress </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Applications (stat.AP); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2312.00379" title="Abstract" id="2312.00379"> arXiv:2312.00379 </a> [<a href="/pdf/2312.00379" title="Download PDF" id="pdf-2312.00379" aria-labelledby="pdf-2312.00379">pdf</a>, <a href="https://arxiv.org/html/2312.00379v1" title="View HTML" id="html-2312.00379" aria-labelledby="html-2312.00379" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00379" title="Other formats" id="oth-2312.00379" aria-labelledby="oth-2312.00379">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Sample Complexity of Contrastive Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Alon,+N">Noga Alon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Avdiukhin,+D">Dmitrii Avdiukhin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Elboim,+D">Dor Elboim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fischer,+O">Orr Fischer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yaroslavtsev,+G">Grigory Yaroslavtsev</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='item36'>[36]</a> <a href ="/abs/2312.00388" title="Abstract" id="2312.00388"> arXiv:2312.00388 </a> [<a href="/pdf/2312.00388" title="Download PDF" id="pdf-2312.00388" aria-labelledby="pdf-2312.00388">pdf</a>, <a href="/format/2312.00388" title="Other formats" id="oth-2312.00388" aria-labelledby="oth-2312.00388">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devices </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+J">Junchen Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+Y">Yurun Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+S">Simeng Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Harris,+I+G">Ian G. Harris</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jyothi,+S+A">Sangeetha Abdu Jyothi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 8 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Distributed, Parallel, and Cluster Computing (cs.DC); Networking and Internet Architecture (cs.NI) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2312.00396" title="Abstract" id="2312.00396"> arXiv:2312.00396 </a> [<a href="/pdf/2312.00396" title="Download PDF" id="pdf-2312.00396" aria-labelledby="pdf-2312.00396">pdf</a>, <a href="https://arxiv.org/html/2312.00396v1" title="View HTML" id="html-2312.00396" aria-labelledby="html-2312.00396" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00396" title="Other formats" id="oth-2312.00396" aria-labelledby="oth-2312.00396">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GFN-SR: Symbolic Regression with Generative Flow Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+S">Sida Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Marinescu,+I">Ioana Marinescu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Musslick,+S">Sebastian Musslick</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by the NeurIPS 2023 AI4Science Workshop </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='item38'>[38]</a> <a href ="/abs/2312.00404" title="Abstract" id="2312.00404"> arXiv:2312.00404 </a> [<a href="/pdf/2312.00404" title="Download PDF" id="pdf-2312.00404" aria-labelledby="pdf-2312.00404">pdf</a>, <a href="https://arxiv.org/html/2312.00404v1" title="View HTML" id="html-2312.00404" aria-labelledby="html-2312.00404" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00404" title="Other formats" id="oth-2312.00404" aria-labelledby="oth-2312.00404">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Causality-Aware Pattern Mining Scheme for Group Activity Recognition in a Pervasive Sensor Space </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+H">Hyunju Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Son,+H">Heesuk Son</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+D">Dongman Lee</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Databases (cs.DB) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2312.00411" title="Abstract" id="2312.00411"> arXiv:2312.00411 </a> [<a href="/pdf/2312.00411" title="Download PDF" id="pdf-2312.00411" aria-labelledby="pdf-2312.00411">pdf</a>, <a href="/format/2312.00411" title="Other formats" id="oth-2312.00411" aria-labelledby="oth-2312.00411">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shu,+Y">Yeshuo Shu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+G">Gangcheng Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+K">Keyi Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tang,+J">Jintong Tang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+L">Liyan Xu</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='item40'>[40]</a> <a href ="/abs/2312.00434" title="Abstract" id="2312.00434"> arXiv:2312.00434 </a> [<a href="/pdf/2312.00434" title="Download PDF" id="pdf-2312.00434" aria-labelledby="pdf-2312.00434">pdf</a>, <a href="https://arxiv.org/html/2312.00434v1" title="View HTML" id="html-2312.00434" aria-labelledby="html-2312.00434" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00434" title="Other formats" id="oth-2312.00434" aria-labelledby="oth-2312.00434">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> PEFTDebias : Capturing debiasing information using PEFTs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Agarwal,+S">Sumit Agarwal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Veerubhotla,+A+S">Aditya Srikanth Veerubhotla</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bansal,+S">Srijan Bansal</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> EMNLP 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computers and Society (cs.CY) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/2312.00471" title="Abstract" id="2312.00471"> arXiv:2312.00471 </a> [<a href="/pdf/2312.00471" title="Download PDF" id="pdf-2312.00471" aria-labelledby="pdf-2312.00471">pdf</a>, <a href="/format/2312.00471" title="Other formats" id="oth-2312.00471" aria-labelledby="oth-2312.00471">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian approach for prompt optimization in pre-trained language models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sabbatella,+A">Antonio Sabbatella</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ponti,+A">Andrea Ponti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Candelieri,+A">Antonio Candelieri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Giordani,+I">Ilaria Giordani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Archetti,+F">Francesco Archetti</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='item42'>[42]</a> <a href ="/abs/2312.00477" title="Abstract" id="2312.00477"> arXiv:2312.00477 </a> [<a href="/pdf/2312.00477" title="Download PDF" id="pdf-2312.00477" aria-labelledby="pdf-2312.00477">pdf</a>, <a href="https://arxiv.org/html/2312.00477v2" title="View HTML" id="html-2312.00477" aria-labelledby="html-2312.00477" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00477" title="Other formats" id="oth-2312.00477" aria-labelledby="oth-2312.00477">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Interpretable Meta-Learning of Physical Systems </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Blanke,+M">Matthieu Blanke</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lelarge,+M">Marc Lelarge</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> The Twelfth International Conference on Learning Representations, ICLR 2024 </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='item43'>[43]</a> <a href ="/abs/2312.00484" title="Abstract" id="2312.00484"> arXiv:2312.00484 </a> [<a href="/pdf/2312.00484" title="Download PDF" id="pdf-2312.00484" aria-labelledby="pdf-2312.00484">pdf</a>, <a href="https://arxiv.org/html/2312.00484v1" title="View HTML" id="html-2312.00484" aria-labelledby="html-2312.00484" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00484" title="Other formats" id="oth-2312.00484" aria-labelledby="oth-2312.00484">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MultiView Independent Component Analysis with Delays </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Heurtebise,+A">Ambroise Heurtebise</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ablin,+P">Pierre Ablin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gramfort,+A">Alexandre Gramfort</a></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='item44'>[44]</a> <a href ="/abs/2312.00485" title="Abstract" id="2312.00485"> arXiv:2312.00485 </a> [<a href="/pdf/2312.00485" title="Download PDF" id="pdf-2312.00485" aria-labelledby="pdf-2312.00485">pdf</a>, <a href="https://arxiv.org/html/2312.00485v1" title="View HTML" id="html-2312.00485" aria-labelledby="html-2312.00485" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00485" title="Other formats" id="oth-2312.00485" aria-labelledby="oth-2312.00485">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Backbone-based Dynamic Graph Spatio-Temporal Network for Epidemic Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mao,+J">Junkai Mao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Han,+Y">Yuexing Han</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tanaka,+G">Gouhei Tanaka</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+B">Bing Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Populations and Evolution (q-bio.PE) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/2312.00486" title="Abstract" id="2312.00486"> arXiv:2312.00486 </a> [<a href="/pdf/2312.00486" title="Download PDF" id="pdf-2312.00486" aria-labelledby="pdf-2312.00486">pdf</a>, <a href="https://arxiv.org/html/2312.00486v2" title="View HTML" id="html-2312.00486" aria-labelledby="html-2312.00486" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00486" title="Other formats" id="oth-2312.00486" aria-labelledby="oth-2312.00486">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> REDUCR: Robust Data Downsampling Using Class Priority Reweighting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bankes,+W">William Bankes</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hughes,+G">George Hughes</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bogunovic,+I">Ilija Bogunovic</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Z">Zi Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Preprint </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='item46'>[46]</a> <a href ="/abs/2312.00502" title="Abstract" id="2312.00502"> arXiv:2312.00502 </a> [<a href="/pdf/2312.00502" title="Download PDF" id="pdf-2312.00502" aria-labelledby="pdf-2312.00502">pdf</a>, <a href="https://arxiv.org/html/2312.00502v6" title="View HTML" id="html-2312.00502" aria-labelledby="html-2312.00502" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00502" title="Other formats" id="oth-2312.00502" aria-labelledby="oth-2312.00502">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ballas,+A">Aristotelis Ballas</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Papapanagiotou,+V">Vasileios Papapanagiotou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Diou,+C">Christos Diou</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted in IEEE ACCESS: <a href="https://doi.org/10.1109/ACCESS.2024.3519297" 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>; Sound (cs.SD); Audio and Speech Processing (eess.AS); Quantitative Methods (q-bio.QM) </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/2312.00516" title="Abstract" id="2312.00516"> arXiv:2312.00516 </a> [<a href="/pdf/2312.00516" title="Download PDF" id="pdf-2312.00516" aria-labelledby="pdf-2312.00516">pdf</a>, <a href="https://arxiv.org/html/2312.00516v3" title="View HTML" id="html-2312.00516" aria-labelledby="html-2312.00516" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00516" title="Other formats" id="oth-2312.00516" aria-labelledby="oth-2312.00516">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+H">Haotian Gao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+R">Renhe Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dong,+Z">Zheng Dong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+J">Jinliang Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+Y">Yuxin Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+X">Xuan Song</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at IJCAI-2024 Main Track </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='item48'>[48]</a> <a href ="/abs/2312.00540" title="Abstract" id="2312.00540"> arXiv:2312.00540 </a> [<a href="/pdf/2312.00540" title="Download PDF" id="pdf-2312.00540" aria-labelledby="pdf-2312.00540">pdf</a>, <a href="https://arxiv.org/html/2312.00540v1" title="View HTML" id="html-2312.00540" aria-labelledby="html-2312.00540" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00540" title="Other formats" id="oth-2312.00540" aria-labelledby="oth-2312.00540">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Target-agnostic Source-free Domain Adaptation for Regression Tasks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=He,+T">Tianlang He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xia,+Z">Zhiqiu Xia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J">Jierun Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+H">Haoliang Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chan,+S+G">S.-H. Gary Chan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by ICDE 2024 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2312.00548" title="Abstract" id="2312.00548"> arXiv:2312.00548 </a> [<a href="/pdf/2312.00548" title="Download PDF" id="pdf-2312.00548" aria-labelledby="pdf-2312.00548">pdf</a>, <a href="/format/2312.00548" title="Other formats" id="oth-2312.00548" aria-labelledby="oth-2312.00548">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Domain Adaptive Imitation Learning with Visual Observation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Choi,+S">Sungho Choi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Han,+S">Seungyul Han</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+W">Woojun Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chae,+J">Jongseong Chae</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jung,+W">Whiyoung Jung</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sung,+Y">Youngchul Sung</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted to NeurIPS 2023 </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); Robotics (cs.RO) </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/2312.00561" title="Abstract" id="2312.00561"> arXiv:2312.00561 </a> [<a href="/pdf/2312.00561" title="Download PDF" id="pdf-2312.00561" aria-labelledby="pdf-2312.00561">pdf</a>, <a href="https://arxiv.org/html/2312.00561v3" title="View HTML" id="html-2312.00561" aria-labelledby="html-2312.00561" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2312.00561" title="Other formats" id="oth-2312.00561" aria-labelledby="oth-2312.00561">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A safe exploration approach to constrained Markov decision processes </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ni,+T">Tingting Ni</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kamgarpour,+M">Maryam Kamgarpour</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 37 pages, 3 figures </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> </dl> <div class='paging'>Total of 2732 entries : <span>1-50</span> <a href=/list/cs.LG/2023-12?skip=50&show=50>51-100</a> <a href=/list/cs.LG/2023-12?skip=100&show=50>101-150</a> <a href=/list/cs.LG/2023-12?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/2023-12?skip=2700&show=50>2701-2732</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/2023-12?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2023-12?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2023-12?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">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; 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