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Machine Learning Feb 2025
<!DOCTYPE html> <html lang="en"> <head> <title>Machine Learning Feb 2025</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/2025-02?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2025-02?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2025-02?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/2502.00021" title="Abstract" id="2502.00021"> arXiv:2502.00021 </a> [<a href="/pdf/2502.00021" title="Download PDF" id="pdf-2502.00021" aria-labelledby="pdf-2502.00021">pdf</a>, <a href="https://arxiv.org/html/2502.00021v1" title="View HTML" id="html-2502.00021" aria-labelledby="html-2502.00021" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00021" title="Other formats" id="oth-2502.00021" aria-labelledby="oth-2502.00021">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> PixelBrax: Learning Continuous Control from Pixels End-to-End on the GPU </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=McInroe,+T">Trevor McInroe</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Garcin,+S">Samuel Garcin</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='item2'>[2]</a> <a href ="/abs/2502.00025" title="Abstract" id="2502.00025"> arXiv:2502.00025 </a> [<a href="/pdf/2502.00025" title="Download PDF" id="pdf-2502.00025" aria-labelledby="pdf-2502.00025">pdf</a>, <a href="/format/2502.00025" title="Other formats" id="oth-2502.00025" aria-labelledby="oth-2502.00025">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Leveraging Large Language Models to Enhance Machine Learning Interpretability and Predictive Performance: A Case Study on Emergency Department Returns for Mental Health Patients </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ahmed,+A">Abdulaziz Ahmed</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saleem,+M">Mohammad Saleem</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Alzeen,+M">Mohammed Alzeen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Birur,+B">Badari Birur</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fargason,+R+E">Rachel E Fargason</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Burk,+B+G">Bradley G Burk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Harkins,+H+R">Hannah Rose Harkins</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Alhassan,+A">Ahmed Alhassan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Al-Garadi,+M+A">Mohammed Ali Al-Garadi</a></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='item3'>[3]</a> <a href ="/abs/2502.00036" title="Abstract" id="2502.00036"> arXiv:2502.00036 </a> [<a href="/pdf/2502.00036" title="Download PDF" id="pdf-2502.00036" aria-labelledby="pdf-2502.00036">pdf</a>, <a href="https://arxiv.org/html/2502.00036v1" title="View HTML" id="html-2502.00036" aria-labelledby="html-2502.00036" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00036" title="Other formats" id="oth-2502.00036" aria-labelledby="oth-2502.00036">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Client Selection in Federated Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Marfo,+W">William Marfo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tosh,+D+K">Deepak K. Tosh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moore,+S+V">Shirley V. Moore</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Distributed, Parallel, and Cluster Computing (cs.DC) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2502.00040" title="Abstract" id="2502.00040"> arXiv:2502.00040 </a> [<a href="/pdf/2502.00040" title="Download PDF" id="pdf-2502.00040" aria-labelledby="pdf-2502.00040">pdf</a>, <a href="https://arxiv.org/html/2502.00040v1" title="View HTML" id="html-2502.00040" aria-labelledby="html-2502.00040" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00040" title="Other formats" id="oth-2502.00040" aria-labelledby="oth-2502.00040">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multi-Objective Reinforcement Learning for Power Grid Topology Control </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lautenbacher,+T">Thomas Lautenbacher</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rajaei,+A">Ali Rajaei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Barbieri,+D">Davide Barbieri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Viebahn,+J">Jan Viebahn</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cremer,+J+L">Jochen L. Cremer</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Systems and Control (eess.SY) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2502.00045" title="Abstract" id="2502.00045"> arXiv:2502.00045 </a> [<a href="/pdf/2502.00045" title="Download PDF" id="pdf-2502.00045" aria-labelledby="pdf-2502.00045">pdf</a>, <a href="https://arxiv.org/html/2502.00045v1" title="View HTML" id="html-2502.00045" aria-labelledby="html-2502.00045" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00045" title="Other formats" id="oth-2502.00045" aria-labelledby="oth-2502.00045">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Restless Multi-armed Bandits under Frequency and Window Constraints for Public Service Inspections </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mao,+Y">Yi Mao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Perrault,+A">Andrew Perrault</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); Computers and Society (cs.CY) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2502.00046" title="Abstract" id="2502.00046"> arXiv:2502.00046 </a> [<a href="/pdf/2502.00046" title="Download PDF" id="pdf-2502.00046" aria-labelledby="pdf-2502.00046">pdf</a>, <a href="https://arxiv.org/html/2502.00046v1" title="View HTML" id="html-2502.00046" aria-labelledby="html-2502.00046" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00046" title="Other formats" id="oth-2502.00046" aria-labelledby="oth-2502.00046">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimization Strategies for Enhancing Resource Efficiency in Transformers & Large Language Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wallace,+T">Tom Wallace</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ezzati-Jivan,+N">Naser Ezzati-Jivan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ombuki-Berman,+B">Beatrice Ombuki-Berman</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for ACM's ICPE 2025 in Short Paper format </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='item7'>[7]</a> <a href ="/abs/2502.00047" title="Abstract" id="2502.00047"> arXiv:2502.00047 </a> [<a href="/pdf/2502.00047" title="Download PDF" id="pdf-2502.00047" aria-labelledby="pdf-2502.00047">pdf</a>, <a href="/format/2502.00047" title="Other formats" id="oth-2502.00047" aria-labelledby="oth-2502.00047">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HadamRNN: Binary and Sparse Ternary Orthogonal RNNs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Foucault,+A">Armand Foucault</a> (IMT, ANITI), <a href="https://arxiv.org/search/cs?searchtype=author&query=Mamalet,+F">Franck Mamalet</a> (ANITI), <a href="https://arxiv.org/search/cs?searchtype=author&query=Malgouyres,+F">Fran莽ois Malgouyres</a> (IMT)</div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> International Conference on Learning Representations (ICLR), Apr 2025, Singapour, Singapore </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/2502.00048" title="Abstract" id="2502.00048"> arXiv:2502.00048 </a> [<a href="/pdf/2502.00048" title="Download PDF" id="pdf-2502.00048" aria-labelledby="pdf-2502.00048">pdf</a>, <a href="https://arxiv.org/html/2502.00048v1" title="View HTML" id="html-2502.00048" aria-labelledby="html-2502.00048" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00048" title="Other formats" id="oth-2502.00048" aria-labelledby="oth-2502.00048">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Contextually Entangled Gradient Mapping for Optimized LLM Comprehension </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sisate,+C">Colin Sisate</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Goldfinch,+A">Alistair Goldfinch</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Waterstone,+V">Vincent Waterstone</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kingsley,+S">Sebastian Kingsley</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Blackthorn,+M">Mariana Blackthorn</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2502.00052" title="Abstract" id="2502.00052"> arXiv:2502.00052 </a> [<a href="/pdf/2502.00052" title="Download PDF" id="pdf-2502.00052" aria-labelledby="pdf-2502.00052">pdf</a>, <a href="/format/2502.00052" title="Other formats" id="oth-2502.00052" aria-labelledby="oth-2502.00052">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Quintana,+G+I">Gonzalo I帽aki Quintana</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vancamberg,+L">Laurence Vancamberg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jugnon,+V">Vincent Jugnon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Desolneux,+A">Agn猫s Desolneux</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mougeot,+M">Mathilde Mougeot</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='item10'>[10]</a> <a href ="/abs/2502.00059" title="Abstract" id="2502.00059"> arXiv:2502.00059 </a> [<a href="/pdf/2502.00059" title="Download PDF" id="pdf-2502.00059" aria-labelledby="pdf-2502.00059">pdf</a>, <a href="https://arxiv.org/html/2502.00059v1" title="View HTML" id="html-2502.00059" aria-labelledby="html-2502.00059" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00059" title="Other formats" id="oth-2502.00059" aria-labelledby="oth-2502.00059">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large Language Models are Few-shot Multivariate Time Series Classifiers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yakun Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Z">Zihao Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+C">Chao Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+X">Xianzhi Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+G">Guandong Xu</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='item11'>[11]</a> <a href ="/abs/2502.00061" title="Abstract" id="2502.00061"> arXiv:2502.00061 </a> [<a href="/pdf/2502.00061" title="Download PDF" id="pdf-2502.00061" aria-labelledby="pdf-2502.00061">pdf</a>, <a href="https://arxiv.org/html/2502.00061v1" title="View HTML" id="html-2502.00061" aria-labelledby="html-2502.00061" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00061" title="Other formats" id="oth-2502.00061" aria-labelledby="oth-2502.00061">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Data to Action: Charting A Data-Driven Path to Combat Antimicrobial Resistance </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Fu,+Q">Qian Fu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yuzhe Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shu,+Y">Yanfeng Shu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ding,+M">Ming Ding</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yao,+L">Lina Yao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+C">Chen Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 29 pages, 3 figures, 4 tables, survey paper </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Populations and Evolution (q-bio.PE) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2502.00088" title="Abstract" id="2502.00088"> arXiv:2502.00088 </a> [<a href="/pdf/2502.00088" title="Download PDF" id="pdf-2502.00088" aria-labelledby="pdf-2502.00088">pdf</a>, <a href="https://arxiv.org/html/2502.00088v1" title="View HTML" id="html-2502.00088" aria-labelledby="html-2502.00088" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00088" title="Other formats" id="oth-2502.00088" aria-labelledby="oth-2502.00088">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Salih,+A+M">Ahmed M. Salih</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='item13'>[13]</a> <a href ="/abs/2502.00108" title="Abstract" id="2502.00108"> arXiv:2502.00108 </a> [<a href="/pdf/2502.00108" title="Download PDF" id="pdf-2502.00108" aria-labelledby="pdf-2502.00108">pdf</a>, <a href="https://arxiv.org/html/2502.00108v1" title="View HTML" id="html-2502.00108" aria-labelledby="html-2502.00108" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00108" title="Other formats" id="oth-2502.00108" aria-labelledby="oth-2502.00108">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Tracking Most Significant Shifts in Infinite-Armed Bandits </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Suk,+J">Joe Suk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+J">Jung-hun Kim</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='item14'>[14]</a> <a href ="/abs/2502.00112" title="Abstract" id="2502.00112"> arXiv:2502.00112 </a> [<a href="/pdf/2502.00112" title="Download PDF" id="pdf-2502.00112" aria-labelledby="pdf-2502.00112">pdf</a>, <a href="https://arxiv.org/html/2502.00112v1" title="View HTML" id="html-2502.00112" aria-labelledby="html-2502.00112" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00112" title="Other formats" id="oth-2502.00112" aria-labelledby="oth-2502.00112">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bernal,+J">Javier Bernal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Torres-Jimenez,+J">Jose Torres-Jimenez</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Research of the National Institute of Standards and Technology Volume 120 (2015) </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) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2502.00140" title="Abstract" id="2502.00140"> arXiv:2502.00140 </a> [<a href="/pdf/2502.00140" title="Download PDF" id="pdf-2502.00140" aria-labelledby="pdf-2502.00140">pdf</a>, <a href="https://arxiv.org/html/2502.00140v1" title="View HTML" id="html-2502.00140" aria-labelledby="html-2502.00140" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00140" title="Other formats" id="oth-2502.00140" aria-labelledby="oth-2502.00140">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+Q">Qin Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+C">Chengjia Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lones,+M">Michael Lones</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pang,+W">Wei Pang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE); Social and Information Networks (cs.SI) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2502.00172" title="Abstract" id="2502.00172"> arXiv:2502.00172 </a> [<a href="/pdf/2502.00172" title="Download PDF" id="pdf-2502.00172" aria-labelledby="pdf-2502.00172">pdf</a>, <a href="/format/2502.00172" title="Other formats" id="oth-2502.00172" aria-labelledby="oth-2502.00172">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Distribution-Specific Agnostic Conditional Classification With Halfspaces </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+J">Jizhou Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Juba,+B">Brendan Juba</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computational Complexity (cs.CC); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2502.00177" title="Abstract" id="2502.00177"> arXiv:2502.00177 </a> [<a href="/pdf/2502.00177" title="Download PDF" id="pdf-2502.00177" aria-labelledby="pdf-2502.00177">pdf</a>, <a href="https://arxiv.org/html/2502.00177v1" title="View HTML" id="html-2502.00177" aria-labelledby="html-2502.00177" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00177" title="Other formats" id="oth-2502.00177" aria-labelledby="oth-2502.00177">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Evaluating Deep Human-in-the-Loop Optimization for Retinal Implants Using Sighted Participants </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Schoinas,+E">Eirini Schoinas</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rastogi,+A">Adyah Rastogi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Carter,+A">Anissa Carter</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Granley,+J">Jacob Granley</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Beyeler,+M">Michael Beyeler</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); Human-Computer Interaction (cs.HC) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2502.00180" title="Abstract" id="2502.00180"> arXiv:2502.00180 </a> [<a href="/pdf/2502.00180" title="Download PDF" id="pdf-2502.00180" aria-labelledby="pdf-2502.00180">pdf</a>, <a href="/format/2502.00180" title="Other formats" id="oth-2502.00180" aria-labelledby="oth-2502.00180">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Designing Scheduling for Diffusion Models via Spectral Analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Benita,+R">Roi Benita</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Elad,+M">Michael Elad</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Keshet,+J">Joseph Keshet</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='item19'>[19]</a> <a href ="/abs/2502.00182" title="Abstract" id="2502.00182"> arXiv:2502.00182 </a> [<a href="/pdf/2502.00182" title="Download PDF" id="pdf-2502.00182" aria-labelledby="pdf-2502.00182">pdf</a>, <a href="https://arxiv.org/html/2502.00182v2" title="View HTML" id="html-2502.00182" aria-labelledby="html-2502.00182" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00182" title="Other formats" id="oth-2502.00182" aria-labelledby="oth-2502.00182">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Seo,+J">Jungwon Seo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Catak,+F+O">Ferhat Ozgur Catak</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rong,+C">Chunming Rong</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 36th Norwegian ICT Conference for Research and Education, NIKT 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='item20'>[20]</a> <a href ="/abs/2502.00190" title="Abstract" id="2502.00190"> arXiv:2502.00190 </a> [<a href="/pdf/2502.00190" title="Download PDF" id="pdf-2502.00190" aria-labelledby="pdf-2502.00190">pdf</a>, <a href="https://arxiv.org/html/2502.00190v1" title="View HTML" id="html-2502.00190" aria-labelledby="html-2502.00190" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00190" title="Other formats" id="oth-2502.00190" aria-labelledby="oth-2502.00190">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Effectiveness of Random Weights in Graph Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bui,+T">Thu Bui</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sch%C3%B6nlieb,+C">Carola-Bibiane Sch枚nlieb</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ribeiro,+B">Bruno Ribeiro</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bevilacqua,+B">Beatrice Bevilacqua</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Eliasof,+M">Moshe Eliasof</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='item21'>[21]</a> <a href ="/abs/2502.00193" title="Abstract" id="2502.00193"> arXiv:2502.00193 </a> [<a href="/pdf/2502.00193" title="Download PDF" id="pdf-2502.00193" aria-labelledby="pdf-2502.00193">pdf</a>, <a href="/format/2502.00193" title="Other formats" id="oth-2502.00193" aria-labelledby="oth-2502.00193">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Egger,+M">Maximilian Egger</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bakshi,+M">Mayank Bakshi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bitar,+R">Rawad Bitar</a></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); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2502.00194" title="Abstract" id="2502.00194"> arXiv:2502.00194 </a> [<a href="/pdf/2502.00194" title="Download PDF" id="pdf-2502.00194" aria-labelledby="pdf-2502.00194">pdf</a>, <a href="/format/2502.00194" title="Other formats" id="oth-2502.00194" aria-labelledby="oth-2502.00194">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Physics-Informed Neural Network based Damage Identification for Truss Railroad Bridges </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shajihan,+A">Althaf Shajihan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mechitov,+K">Kirill Mechitov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chowdhary,+G">Girish Chowdhary</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Spencer,+B+F">Billie F. Spencer Jr</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 30 pages, 15 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computational Physics (physics.comp-ph) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2502.00197" title="Abstract" id="2502.00197"> arXiv:2502.00197 </a> [<a href="/pdf/2502.00197" title="Download PDF" id="pdf-2502.00197" aria-labelledby="pdf-2502.00197">pdf</a>, <a href="https://arxiv.org/html/2502.00197v1" title="View HTML" id="html-2502.00197" aria-labelledby="html-2502.00197" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00197" title="Other formats" id="oth-2502.00197" aria-labelledby="oth-2502.00197">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Model Successor Functions </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chang,+Y">Yingshan Chang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bisk,+Y">Yonatan Bisk</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/2502.00201" title="Abstract" id="2502.00201"> arXiv:2502.00201 </a> [<a href="/pdf/2502.00201" title="Download PDF" id="pdf-2502.00201" aria-labelledby="pdf-2502.00201">pdf</a>, <a href="https://arxiv.org/html/2502.00201v1" title="View HTML" id="html-2502.00201" aria-labelledby="html-2502.00201" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00201" title="Other formats" id="oth-2502.00201" aria-labelledby="oth-2502.00201">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Year-over-Year Developments in Financial Fraud Detection via Deep Learning: A Systematic Literature Review </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yisong Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+C">Chuqing Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+Y">Yixin Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nie,+C">Chuanhao Nie</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Statistical Finance (q-fin.ST) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2502.00203" title="Abstract" id="2502.00203"> arXiv:2502.00203 </a> [<a href="/pdf/2502.00203" title="Download PDF" id="pdf-2502.00203" aria-labelledby="pdf-2502.00203">pdf</a>, <a href="https://arxiv.org/html/2502.00203v2" title="View HTML" id="html-2502.00203" aria-labelledby="html-2502.00203" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00203" title="Other formats" id="oth-2502.00203" aria-labelledby="oth-2502.00203">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+S">Shengyang Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yian Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bukharin,+A">Alexander Bukharin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mosallanezhad,+D">David Mosallanezhad</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zeng,+J">Jiaqi Zeng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Singhal,+S">Soumye Singhal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shen,+G">Gerald Shen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Renduchintala,+A">Adithya Renduchintala</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Konuk,+T">Tugrul Konuk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dong,+Y">Yi Dong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Z">Zhilin Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chichkov,+D">Dmitry Chichkov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Delalleau,+O">Olivier Delalleau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kuchaiev,+O">Oleksii Kuchaiev</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 4 figures; update author names </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/2502.00204" title="Abstract" id="2502.00204"> arXiv:2502.00204 </a> [<a href="/pdf/2502.00204" title="Download PDF" id="pdf-2502.00204" aria-labelledby="pdf-2502.00204">pdf</a>, <a href="https://arxiv.org/html/2502.00204v1" title="View HTML" id="html-2502.00204" aria-labelledby="html-2502.00204" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00204" title="Other formats" id="oth-2502.00204" aria-labelledby="oth-2502.00204">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Balcan,+M">Maria-Florina Balcan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bernasconi,+M">Martino Bernasconi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Castiglioni,+M">Matteo Castiglioni</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Celli,+A">Andrea Celli</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Harris,+K">Keegan Harris</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+Z+S">Zhiwei Steven Wu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computer Science and Game Theory (cs.GT) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/2502.00206" title="Abstract" id="2502.00206"> arXiv:2502.00206 </a> [<a href="/pdf/2502.00206" title="Download PDF" id="pdf-2502.00206" aria-labelledby="pdf-2502.00206">pdf</a>, <a href="https://arxiv.org/html/2502.00206v1" title="View HTML" id="html-2502.00206" aria-labelledby="html-2502.00206" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00206" title="Other formats" id="oth-2502.00206" aria-labelledby="oth-2502.00206">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> BICompFL: Stochastic Federated Learning with Bi-Directional Compression </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Egger,+M">Maximilian Egger</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bitar,+R">Rawad Bitar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wachter-Zeh,+A">Antonia Wachter-Zeh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Weinberger,+N">Nir Weinberger</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=G%C3%BCnd%C3%BCz,+D">Deniz G眉nd眉z</a></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); Information Theory (cs.IT); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/2502.00212" title="Abstract" id="2502.00212"> arXiv:2502.00212 </a> [<a href="/pdf/2502.00212" title="Download PDF" id="pdf-2502.00212" aria-labelledby="pdf-2502.00212">pdf</a>, <a href="https://arxiv.org/html/2502.00212v3" title="View HTML" id="html-2502.00212" aria-labelledby="html-2502.00212" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00212" title="Other formats" id="oth-2502.00212" aria-labelledby="oth-2502.00212">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dong,+K">Kefan Dong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+T">Tengyu Ma</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 23 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Logic in Computer Science (cs.LO) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2502.00213" title="Abstract" id="2502.00213"> arXiv:2502.00213 </a> [<a href="/pdf/2502.00213" title="Download PDF" id="pdf-2502.00213" aria-labelledby="pdf-2502.00213">pdf</a>, <a href="https://arxiv.org/html/2502.00213v1" title="View HTML" id="html-2502.00213" aria-labelledby="html-2502.00213" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00213" title="Other formats" id="oth-2502.00213" aria-labelledby="oth-2502.00213">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Understanding Why Adam Outperforms SGD: Gradient Heterogeneity in Transformers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tomihari,+A">Akiyoshi Tomihari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sato,+I">Issei Sato</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2502.00217" title="Abstract" id="2502.00217"> arXiv:2502.00217 </a> [<a href="/pdf/2502.00217" title="Download PDF" id="pdf-2502.00217" aria-labelledby="pdf-2502.00217">pdf</a>, <a href="https://arxiv.org/html/2502.00217v1" title="View HTML" id="html-2502.00217" aria-labelledby="html-2502.00217" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00217" title="Other formats" id="oth-2502.00217" aria-labelledby="oth-2502.00217">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fantastic Multi-Task Gradient Updates and How to Find Them In a Cone </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hassanpour,+N">Negar Hassanpour</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Janjua,+M+K">Muhammad Kamran Janjua</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+K">Kunlin Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lavasani,+S">Sepehr Lavasani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+X">Xiaowen Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+C">Chunhua Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+C">Chao Gao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 7 figures, 5 tables </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='item31'>[31]</a> <a href ="/abs/2502.00220" title="Abstract" id="2502.00220"> arXiv:2502.00220 </a> [<a href="/pdf/2502.00220" title="Download PDF" id="pdf-2502.00220" aria-labelledby="pdf-2502.00220">pdf</a>, <a href="https://arxiv.org/html/2502.00220v1" title="View HTML" id="html-2502.00220" aria-labelledby="html-2502.00220" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00220" title="Other formats" id="oth-2502.00220" aria-labelledby="oth-2502.00220">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Algorithmic Clustering based on String Compression to Extract P300 Structure in EEG Signals </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sarasa,+G">Guillermo Sarasa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Granados,+A">Ana Granados</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rodr%C3%ADguez,+F+B">Francisco B Rodr铆guez</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Computer Methods and Programs in Biomedicine 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Theory (cs.IT); Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/2502.00225" title="Abstract" id="2502.00225"> arXiv:2502.00225 </a> [<a href="/pdf/2502.00225" title="Download PDF" id="pdf-2502.00225" aria-labelledby="pdf-2502.00225">pdf</a>, <a href="https://arxiv.org/html/2502.00225v1" title="View HTML" id="html-2502.00225" aria-labelledby="html-2502.00225" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00225" title="Other formats" id="oth-2502.00225" aria-labelledby="oth-2502.00225">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Should You Use Your Large Language Model to Explore or Exploit? </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Harris,+K">Keegan Harris</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Slivkins,+A">Aleksandrs Slivkins</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2502.00226" title="Abstract" id="2502.00226"> arXiv:2502.00226 </a> [<a href="/pdf/2502.00226" title="Download PDF" id="pdf-2502.00226" aria-labelledby="pdf-2502.00226">pdf</a>, <a href="https://arxiv.org/html/2502.00226v1" title="View HTML" id="html-2502.00226" aria-labelledby="html-2502.00226" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00226" title="Other formats" id="oth-2502.00226" aria-labelledby="oth-2502.00226">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HackerRank-ASTRA: Evaluating Correctness & Consistency of Large Language Models on cross-domain multi-file project problems </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xing,+J">Jun Xing</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bhatia,+M">Mayur Bhatia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Phulwani,+S">Sahil Phulwani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Suresh,+D">Darshan Suresh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Matta,+R">Rafik Matta</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 24 pages, 25 figures </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='item34'>[34]</a> <a href ="/abs/2502.00234" title="Abstract" id="2502.00234"> arXiv:2502.00234 </a> [<a href="/pdf/2502.00234" title="Download PDF" id="pdf-2502.00234" aria-labelledby="pdf-2502.00234">pdf</a>, <a href="https://arxiv.org/html/2502.00234v1" title="View HTML" id="html-2502.00234" aria-labelledby="html-2502.00234" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00234" title="Other formats" id="oth-2502.00234" aria-labelledby="oth-2502.00234">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+Y">Yinuo Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+H">Haoxuan Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+Y">Yuchen Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+W">Wei Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yongxin Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rotskoff,+G+M">Grant M. Rotskoff</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tao,+M">Molei Tao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ying,+L">Lexing Ying</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 38 pages, 7 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); Numerical Analysis (math.NA); Computational Physics (physics.comp-ph); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2502.00241" title="Abstract" id="2502.00241"> arXiv:2502.00241 </a> [<a href="/pdf/2502.00241" title="Download PDF" id="pdf-2502.00241" aria-labelledby="pdf-2502.00241">pdf</a>, <a href="https://arxiv.org/html/2502.00241v1" title="View HTML" id="html-2502.00241" aria-labelledby="html-2502.00241" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00241" title="Other formats" id="oth-2502.00241" aria-labelledby="oth-2502.00241">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Mordal: Automated Pretrained Model Selection for Vision Language Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=He,+S">Shiqi He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jang,+I">Insu Jang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chowdhury,+M">Mosharaf Chowdhury</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2502.00245" title="Abstract" id="2502.00245"> arXiv:2502.00245 </a> [<a href="/pdf/2502.00245" title="Download PDF" id="pdf-2502.00245" aria-labelledby="pdf-2502.00245">pdf</a>, <a href="https://arxiv.org/html/2502.00245v1" title="View HTML" id="html-2502.00245" aria-labelledby="html-2502.00245" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00245" title="Other formats" id="oth-2502.00245" aria-labelledby="oth-2502.00245">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zou,+T">Tianyuan Zou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yang Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+P">Peng Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiong,+Y">Yufei Xiong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+J">Jianqing Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+J">Jingjing Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ye,+X">Xiaozhou Ye</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ouyang,+Y">Ye Ouyang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Ya-Qin Zhang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 11 tables, 7 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='item37'>[37]</a> <a href ="/abs/2502.00258" title="Abstract" id="2502.00258"> arXiv:2502.00258 </a> [<a href="/pdf/2502.00258" title="Download PDF" id="pdf-2502.00258" aria-labelledby="pdf-2502.00258">pdf</a>, <a href="https://arxiv.org/html/2502.00258v1" title="View HTML" id="html-2502.00258" aria-labelledby="html-2502.00258" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00258" title="Other formats" id="oth-2502.00258" aria-labelledby="oth-2502.00258">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+H">Hongyi Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saha,+R">Rajarshi Saha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jia,+Z">Zhen Jia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Park,+Y">Youngsuk Park</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+J">Jiaji Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sabach,+S">Shoham Sabach</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yu-Xiang Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Karypis,+G">George Karypis</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) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2502.00264" title="Abstract" id="2502.00264"> arXiv:2502.00264 </a> [<a href="/pdf/2502.00264" title="Download PDF" id="pdf-2502.00264" aria-labelledby="pdf-2502.00264">pdf</a>, <a href="https://arxiv.org/html/2502.00264v1" title="View HTML" id="html-2502.00264" aria-labelledby="html-2502.00264" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00264" title="Other formats" id="oth-2502.00264" aria-labelledby="oth-2502.00264">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+B">Binchi Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+Z">Zaiyi Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Z">Zhengzhang Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jundong Li</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='item39'>[39]</a> <a href ="/abs/2502.00270" title="Abstract" id="2502.00270"> arXiv:2502.00270 </a> [<a href="/pdf/2502.00270" title="Download PDF" id="pdf-2502.00270" aria-labelledby="pdf-2502.00270">pdf</a>, <a href="https://arxiv.org/html/2502.00270v1" title="View HTML" id="html-2502.00270" aria-labelledby="html-2502.00270" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00270" title="Other formats" id="oth-2502.00270" aria-labelledby="oth-2502.00270">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Z">Zhiliang Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lau,+G+K+R">Gregory Kang Ruey Lau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Foo,+C">Chuan-Sheng Foo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Low,+B+K+H">Bryan Kian Hsiang Low</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='item40'>[40]</a> <a href ="/abs/2502.00277" title="Abstract" id="2502.00277"> arXiv:2502.00277 </a> [<a href="/pdf/2502.00277" title="Download PDF" id="pdf-2502.00277" aria-labelledby="pdf-2502.00277">pdf</a>, <a href="https://arxiv.org/html/2502.00277v1" title="View HTML" id="html-2502.00277" aria-labelledby="html-2502.00277" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00277" title="Other formats" id="oth-2502.00277" aria-labelledby="oth-2502.00277">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Regularized Langevin Dynamics for Combinatorial Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Feng,+S">Shengyu Feng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yiming Yang</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='item41'>[41]</a> <a href ="/abs/2502.00279" title="Abstract" id="2502.00279"> arXiv:2502.00279 </a> [<a href="/pdf/2502.00279" title="Download PDF" id="pdf-2502.00279" aria-labelledby="pdf-2502.00279">pdf</a>, <a href="https://arxiv.org/html/2502.00279v1" title="View HTML" id="html-2502.00279" aria-labelledby="html-2502.00279" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00279" title="Other formats" id="oth-2502.00279" aria-labelledby="oth-2502.00279">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improving realistic semi-supervised learning with doubly robust estimation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Pham,+K">Khiem Pham</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Herrmann,+C">Charles Herrmann</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zabih,+R">Ramin Zabih</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='item42'>[42]</a> <a href ="/abs/2502.00280" title="Abstract" id="2502.00280"> arXiv:2502.00280 </a> [<a href="/pdf/2502.00280" title="Download PDF" id="pdf-2502.00280" aria-labelledby="pdf-2502.00280">pdf</a>, <a href="https://arxiv.org/html/2502.00280v1" title="View HTML" id="html-2502.00280" aria-labelledby="html-2502.00280" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00280" title="Other formats" id="oth-2502.00280" aria-labelledby="oth-2502.00280">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the study of frequency control and spectral bias in Wavelet-Based Kolmogorov Arnold networks: A path to physics-informed KANs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Meshir,+J+D">Juan Daniel Meshir</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Palafox,+A">Abel Palafox</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guerrero,+E+A">Edgar Alejandro Guerrero</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 29 pages, 13 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Numerical Analysis (math.NA) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2502.00281" title="Abstract" id="2502.00281"> arXiv:2502.00281 </a> [<a href="/pdf/2502.00281" title="Download PDF" id="pdf-2502.00281" aria-labelledby="pdf-2502.00281">pdf</a>, <a href="https://arxiv.org/html/2502.00281v1" title="View HTML" id="html-2502.00281" aria-labelledby="html-2502.00281" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00281" title="Other formats" id="oth-2502.00281" aria-labelledby="oth-2502.00281">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sigmoid Self-Attention is Better than Softmax Self-Attention: A Mixture-of-Experts Perspective </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Yan,+F">Fanqi Yan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nguyen,+H">Huy Nguyen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Akbarian,+P">Pedram Akbarian</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ho,+N">Nhat Ho</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rinaldo,+A">Alessandro Rinaldo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Fanqi Yan, Huy Nguyen contributed equally to this work. 51 pages, 2 figures, 3 tables </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='item44'>[44]</a> <a href ="/abs/2502.00282" title="Abstract" id="2502.00282"> arXiv:2502.00282 </a> [<a href="/pdf/2502.00282" title="Download PDF" id="pdf-2502.00282" aria-labelledby="pdf-2502.00282">pdf</a>, <a href="https://arxiv.org/html/2502.00282v1" title="View HTML" id="html-2502.00282" aria-labelledby="html-2502.00282" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00282" title="Other formats" id="oth-2502.00282" aria-labelledby="oth-2502.00282">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GraphMinNet: Learning Dependencies in Graphs with Light Complexity Minimal Architecture </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ahamed,+M+A">Md Atik Ahamed</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cheng,+A">Andrew Cheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ye,+Q">Qiang Ye</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cheng,+Q">Qiang Cheng</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='item45'>[45]</a> <a href ="/abs/2502.00285" title="Abstract" id="2502.00285"> arXiv:2502.00285 </a> [<a href="/pdf/2502.00285" title="Download PDF" id="pdf-2502.00285" aria-labelledby="pdf-2502.00285">pdf</a>, <a href="https://arxiv.org/html/2502.00285v1" title="View HTML" id="html-2502.00285" aria-labelledby="html-2502.00285" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00285" title="Other formats" id="oth-2502.00285" aria-labelledby="oth-2502.00285">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> K Nearest Neighbor-Guided Trajectory Similarity Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chang,+Y">Yanchuan Chang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cai,+X">Xu Cai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jensen,+C+S">Christian S. Jensen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Qi,+J">Jianzhong Qi</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); Databases (cs.DB) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/2502.00288" title="Abstract" id="2502.00288"> arXiv:2502.00288 </a> [<a href="/pdf/2502.00288" title="Download PDF" id="pdf-2502.00288" aria-labelledby="pdf-2502.00288">pdf</a>, <a href="https://arxiv.org/html/2502.00288v1" title="View HTML" id="html-2502.00288" aria-labelledby="html-2502.00288" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00288" title="Other formats" id="oth-2502.00288" aria-labelledby="oth-2502.00288">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+J">Jijia Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+F">Feng Gao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liao,+Q">Qingmin Liao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+C">Chao Yu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yu Wang</a></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='item47'>[47]</a> <a href ="/abs/2502.00298" title="Abstract" id="2502.00298"> arXiv:2502.00298 </a> [<a href="/pdf/2502.00298" title="Download PDF" id="pdf-2502.00298" aria-labelledby="pdf-2502.00298">pdf</a>, <a href="https://arxiv.org/html/2502.00298v2" title="View HTML" id="html-2502.00298" aria-labelledby="html-2502.00298" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00298" title="Other formats" id="oth-2502.00298" aria-labelledby="oth-2502.00298">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Price of Linear Time: Error Analysis of Structured Kernel Interpolation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Moreno,+A">Alexander Moreno</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiao,+J">Justin Xiao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mei,+J">Jonathan Mei</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='item48'>[48]</a> <a href ="/abs/2502.00300" title="Abstract" id="2502.00300"> arXiv:2502.00300 </a> [<a href="/pdf/2502.00300" title="Download PDF" id="pdf-2502.00300" aria-labelledby="pdf-2502.00300">pdf</a>, <a href="/format/2502.00300" title="Other formats" id="oth-2502.00300" aria-labelledby="oth-2502.00300">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Uncertainty Quantification of Wind Gust Predictions in the Northeast US: An Evidential Neural Network and Explainable Artificial Intelligence Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jahan,+I">Israt Jahan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schreck,+J+S">John S. Schreck</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gagne,+D+J">David John Gagne</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Becker,+C">Charlie Becker</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Astitha,+M">Marina Astitha</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Main body 27 pages with 12 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Atmospheric and Oceanic Physics (physics.ao-ph); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2502.00304" title="Abstract" id="2502.00304"> arXiv:2502.00304 </a> [<a href="/pdf/2502.00304" title="Download PDF" id="pdf-2502.00304" aria-labelledby="pdf-2502.00304">pdf</a>, <a href="https://arxiv.org/html/2502.00304v1" title="View HTML" id="html-2502.00304" aria-labelledby="html-2502.00304" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00304" title="Other formats" id="oth-2502.00304" aria-labelledby="oth-2502.00304">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HoP: Homeomorphic Polar Learning for Hard Constrained Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+K">Ke Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+H">Hanwen Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+J">Jin Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+H">Haijian Sun</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> in submission </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='item50'>[50]</a> <a href ="/abs/2502.00311" title="Abstract" id="2502.00311"> arXiv:2502.00311 </a> [<a href="/pdf/2502.00311" title="Download PDF" id="pdf-2502.00311" aria-labelledby="pdf-2502.00311">pdf</a>, <a href="https://arxiv.org/html/2502.00311v1" title="View HTML" id="html-2502.00311" aria-labelledby="html-2502.00311" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.00311" title="Other formats" id="oth-2502.00311" aria-labelledby="oth-2502.00311">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sparse Gradient Compression for Fine-Tuning Large Language Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+D+H">David H. Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Amiri,+M+M">Mohammad Mohammadi Amiri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pedapati,+T">Tejaswini Pedapati</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chaudhury,+S">Subhajit Chaudhury</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+P">Pin-Yu Chen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> </dl> <div class='paging'>Total of 4296 entries : <span>1-50</span> <a href=/list/cs.LG/2025-02?skip=50&show=50>51-100</a> <a href=/list/cs.LG/2025-02?skip=100&show=50>101-150</a> <a href=/list/cs.LG/2025-02?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/2025-02?skip=4250&show=50>4251-4296</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/2025-02?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/2025-02?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/2025-02?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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