Machine Learning

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href="/list/stat.ML/recent?skip=94&show=50"> Fri, 14 Mar 2025 </a> </li></ul> <p>See today's <a id="new-stat.ML" aria-labelledby="new-stat.ML" href="/list/stat.ML/new">new</a> changes</p> <div class='paging'>Total of 110 entries : <span>1-50</span> <a href=/list/stat.ML/recent?skip=50&show=50>51-100</a> <a href=/list/stat.ML/recent?skip=100&show=50>101-110</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat.ML/recent?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat.ML/recent?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat.ML/recent?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <h3>Thu, 20 Mar 2025 (showing 11 of 11 entries )</h3> <dt> <a name='item1'>[1]</a> <a href ="/abs/2503.15355" title="Abstract" id="2503.15355"> arXiv:2503.15355 </a> [<a href="/pdf/2503.15355" title="Download PDF" id="pdf-2503.15355" aria-labelledby="pdf-2503.15355">pdf</a>, <a href="https://arxiv.org/html/2503.15355v1" title="View HTML" id="html-2503.15355" aria-labelledby="html-2503.15355" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15355" title="Other formats" id="oth-2503.15355" aria-labelledby="oth-2503.15355">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robustness of Nonlinear Representation Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Buchholz,+S">Simon Buchholz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sch%C3%B6lkopf,+B">Bernhard Sch枚lkopf</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 37 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of the 41st International Conference on Machine Learning, PMLR 235:4785-4821, 2024 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2503.15210" title="Abstract" id="2503.15210"> arXiv:2503.15210 </a> [<a href="/pdf/2503.15210" title="Download PDF" id="pdf-2503.15210" aria-labelledby="pdf-2503.15210">pdf</a>, <a href="https://arxiv.org/html/2503.15210v1" title="View HTML" id="html-2503.15210" aria-labelledby="html-2503.15210" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15210" title="Other formats" id="oth-2503.15210" aria-labelledby="oth-2503.15210">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Online federated learning framework for classification </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Guo,+W">Wenxing Guo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Xie,+J">Jinhan Xie</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lu,+J">Jianya Lu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=jiang,+B">Bei jiang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dai,+H">Hongsheng Dai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kong,+L">Linglong Kong</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2503.15160" title="Abstract" id="2503.15160"> arXiv:2503.15160 </a> [<a href="/pdf/2503.15160" title="Download PDF" id="pdf-2503.15160" aria-labelledby="pdf-2503.15160">pdf</a>, <a href="https://arxiv.org/html/2503.15160v1" title="View HTML" id="html-2503.15160" aria-labelledby="html-2503.15160" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15160" title="Other formats" id="oth-2503.15160" aria-labelledby="oth-2503.15160">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonlinear Bayesian Update via Ensemble Kernel Regression with Clustering and Subsampling </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lee,+Y">Yoonsang Lee</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, four figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Probability (math.PR); Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2503.15107" title="Abstract" id="2503.15107"> arXiv:2503.15107 </a> [<a href="/pdf/2503.15107" title="Download PDF" id="pdf-2503.15107" aria-labelledby="pdf-2503.15107">pdf</a>, <a href="https://arxiv.org/html/2503.15107v1" title="View HTML" id="html-2503.15107" aria-labelledby="html-2503.15107" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15107" title="Other formats" id="oth-2503.15107" aria-labelledby="oth-2503.15107">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Interpretability of Graph Neural Networks to Assert Effects of Global Change Drivers on Ecological Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Anakok,+E">Emre Anakok</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Barbillon,+P">Pierre Barbillon</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fontaine,+C">Colin Fontaine</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Thebault,+E">Elisa Thebault</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2503.14795" title="Abstract" id="2503.14795"> arXiv:2503.14795 </a> [<a href="/pdf/2503.14795" title="Download PDF" id="pdf-2503.14795" aria-labelledby="pdf-2503.14795">pdf</a>, <a href="https://arxiv.org/html/2503.14795v1" title="View HTML" id="html-2503.14795" aria-labelledby="html-2503.14795" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14795" title="Other formats" id="oth-2503.14795" aria-labelledby="oth-2503.14795">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Hardness of Validating Observational Studies with Experimental Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Fawkes,+J">Jake Fawkes</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=O'Riordan,+M">Michael O'Riordan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vlontzos,+A">Athanasios Vlontzos</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Corcoll,+O">Oriol Corcoll</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gilligan-Lee,+C+M">Ciar谩n Mark Gilligan-Lee</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published at AISTATS 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2503.14710" title="Abstract" id="2503.14710"> arXiv:2503.14710 </a> [<a href="/pdf/2503.14710" title="Download PDF" id="pdf-2503.14710" aria-labelledby="pdf-2503.14710">pdf</a>, <a href="https://arxiv.org/html/2503.14710v1" title="View HTML" id="html-2503.14710" aria-labelledby="html-2503.14710" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14710" title="Other formats" id="oth-2503.14710" aria-labelledby="oth-2503.14710">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Variational Autoencoded Multivariate Spatial Fay-Herriot Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Z">Zhenhua Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Parker,+P+A">Paul A. Parker</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Holan,+S+H">Scott H. Holan</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2503.15477" title="Abstract" id="2503.15477"> arXiv:2503.15477 </a> (cross-list from cs.LG) [<a href="/pdf/2503.15477" title="Download PDF" id="pdf-2503.15477" aria-labelledby="pdf-2503.15477">pdf</a>, <a href="https://arxiv.org/html/2503.15477v1" title="View HTML" id="html-2503.15477" aria-labelledby="html-2503.15477" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15477" title="Other formats" id="oth-2503.15477" aria-labelledby="oth-2503.15477">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> What Makes a Reward Model a Good Teacher? An Optimization Perspective </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Razin,+N">Noam Razin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Z">Zixuan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Strauss,+H">Hubert Strauss</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wei,+S">Stanley Wei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+J+D">Jason D. Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Arora,+S">Sanjeev Arora</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Code available at <a href="https://github.com/princeton-pli/what-makes-good-rm" 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>; Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2503.14717" title="Abstract" id="2503.14717"> arXiv:2503.14717 </a> (cross-list from math.ST) [<a href="/pdf/2503.14717" title="Download PDF" id="pdf-2503.14717" aria-labelledby="pdf-2503.14717">pdf</a>, <a href="https://arxiv.org/html/2503.14717v1" title="View HTML" id="html-2503.14717" aria-labelledby="html-2503.14717" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14717" title="Other formats" id="oth-2503.14717" aria-labelledby="oth-2503.14717">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Precise Asymptotics of Universal Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Takatsu,+K">Kenta Takatsu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2503.14549" title="Abstract" id="2503.14549"> arXiv:2503.14549 </a> (cross-list from cs.LG) [<a href="/pdf/2503.14549" title="Download PDF" id="pdf-2503.14549" aria-labelledby="pdf-2503.14549">pdf</a>, <a href="https://arxiv.org/html/2503.14549v1" title="View HTML" id="html-2503.14549" aria-labelledby="html-2503.14549" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14549" title="Other formats" id="oth-2503.14549" aria-labelledby="oth-2503.14549">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sampling Decisions </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chertkov,+M">Michael Chertkov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ahn,+S">Sungsoo Ahn</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Behjoo,+H">Hamidreza Behjoo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 6 pages, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Statistical Mechanics (cond-mat.stat-mech); Artificial Intelligence (cs.AI); Systems and Control (eess.SY); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2503.14525" title="Abstract" id="2503.14525"> arXiv:2503.14525 </a> (cross-list from eess.IV) [<a href="/pdf/2503.14525" title="Download PDF" id="pdf-2503.14525" aria-labelledby="pdf-2503.14525">pdf</a>, <a href="https://arxiv.org/html/2503.14525v1" title="View HTML" id="html-2503.14525" aria-labelledby="html-2503.14525" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14525" title="Other formats" id="oth-2503.14525" aria-labelledby="oth-2503.14525">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Spline refinement with differentiable rendering </div> <div class='list-authors'><a href="https://arxiv.org/search/eess?searchtype=author&query=Zdyb,+F">Frans Zdyb</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Alonso,+A">Albert Alonso</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Kirkegaard,+J+B">Julius B. Kirkegaard</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Image and Video Processing (eess.IV)</span>; Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Applications (stat.AP); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2503.14512" title="Abstract" id="2503.14512"> arXiv:2503.14512 </a> (cross-list from q-bio.QM) [<a href="/pdf/2503.14512" title="Download PDF" id="pdf-2503.14512" aria-labelledby="pdf-2503.14512">pdf</a>, <a href="/format/2503.14512" title="Other formats" id="oth-2503.14512" aria-labelledby="oth-2503.14512">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Machine learning algorithms to predict stroke in China based on causal inference of time series analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/q-bio?searchtype=author&query=Zheng,+Q">Qizhi Zheng</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Zhao,+A">Ayang Zhao</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Wang,+X">Xinzhu Wang</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Bai,+Y">Yanhong Bai</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Wang,+Z">Zikun Wang</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Wang,+X">Xiuying Wang</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Zeng,+X">Xianzhang Zeng</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Dong,+G">Guanghui Dong</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantitative Methods (q-bio.QM)</span>; Machine Learning (cs.LG); Applications (stat.AP); Machine Learning (stat.ML) </div> </div> </dd> </dl> <dl id='articles'> <h3>Wed, 19 Mar 2025 (showing 20 of 20 entries )</h3> <dt> <a name='item12'>[12]</a> <a href ="/abs/2503.14459" title="Abstract" id="2503.14459"> arXiv:2503.14459 </a> [<a href="/pdf/2503.14459" title="Download PDF" id="pdf-2503.14459" aria-labelledby="pdf-2503.14459">pdf</a>, <a href="https://arxiv.org/html/2503.14459v1" title="View HTML" id="html-2503.14459" aria-labelledby="html-2503.14459" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14459" title="Other formats" id="oth-2503.14459" aria-labelledby="oth-2503.14459">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Doubly robust identification of treatment effects from multiple environments </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=De+Bartolomeis,+P">Piersilvio De Bartolomeis</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kostin,+J">Julia Kostin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Abad,+J">Javier Abad</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yixin Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+F">Fanny Yang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for presentation at the International Conference on Learning Representations (ICLR) 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2503.14453" title="Abstract" id="2503.14453"> arXiv:2503.14453 </a> [<a href="/pdf/2503.14453" title="Download PDF" id="pdf-2503.14453" aria-labelledby="pdf-2503.14453">pdf</a>, <a href="https://arxiv.org/html/2503.14453v1" title="View HTML" id="html-2503.14453" aria-labelledby="html-2503.14453" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14453" title="Other formats" id="oth-2503.14453" aria-labelledby="oth-2503.14453">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Online Conformal Probabilistic Numerics via Adaptive Edge-Cloud Offloading </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hou,+Q">Qiushuo Hou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Park,+S">Sangwoo Park</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zecchin,+M">Matteo Zecchin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cai,+Y">Yunlong Cai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yu,+G">Guanding Yu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Simeone,+O">Osvaldo Simeone</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This paper has been submitted to a conference </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2503.14381" title="Abstract" id="2503.14381"> arXiv:2503.14381 </a> [<a href="/pdf/2503.14381" title="Download PDF" id="pdf-2503.14381" aria-labelledby="pdf-2503.14381">pdf</a>, <a href="/format/2503.14381" title="Other formats" id="oth-2503.14381" aria-labelledby="oth-2503.14381">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimizing High-Dimensional Oblique Splits </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chi,+C">Chien-Ming Chi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 79 pages, 9 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Statistics Theory (math.ST); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2503.14121" title="Abstract" id="2503.14121"> arXiv:2503.14121 </a> [<a href="/pdf/2503.14121" title="Download PDF" id="pdf-2503.14121" aria-labelledby="pdf-2503.14121">pdf</a>, <a href="/format/2503.14121" title="Other formats" id="oth-2503.14121" aria-labelledby="oth-2503.14121">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+Y">Yizhou Xu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Maillard,+A">Antoine Maillard</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zdeborov%C3%A1,+L">Lenka Zdeborov谩</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Krzakala,+F">Florent Krzakala</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Disordered Systems and Neural Networks (cond-mat.dis-nn); Information Theory (cs.IT); Machine Learning (cs.LG); Probability (math.PR) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2503.14045" title="Abstract" id="2503.14045"> arXiv:2503.14045 </a> [<a href="/pdf/2503.14045" title="Download PDF" id="pdf-2503.14045" aria-labelledby="pdf-2503.14045">pdf</a>, <a href="/format/2503.14045" title="Other formats" id="oth-2503.14045" aria-labelledby="oth-2503.14045">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Empirical risk minimization algorithm for multiclass classification of S.D.E. paths </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Denis,+C">Christophe Denis</a> (SAMM), <a href="https://arxiv.org/search/stat?searchtype=author&query=Mintsa,+E+E">Eddy Ella Mintsa</a> (LAMA)</div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2503.13791" title="Abstract" id="2503.13791"> arXiv:2503.13791 </a> [<a href="/pdf/2503.13791" title="Download PDF" id="pdf-2503.13791" aria-labelledby="pdf-2503.13791">pdf</a>, <a href="/format/2503.13791" title="Other formats" id="oth-2503.13791" aria-labelledby="oth-2503.13791">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> ROCK: A variational formulation for occupation kernel methods in Reproducing Kernel Hilbert Spaces </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rielly,+V">Victor Rielly</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lahouel,+K">Kamel Lahouel</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nguyen,+C">Chau Nguyen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jedynak,+B">Bruno Jedynak</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2503.13751" title="Abstract" id="2503.13751"> arXiv:2503.13751 </a> [<a href="/pdf/2503.13751" title="Download PDF" id="pdf-2503.13751" aria-labelledby="pdf-2503.13751">pdf</a>, <a href="/format/2503.13751" title="Other formats" id="oth-2503.13751" aria-labelledby="oth-2503.13751">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimizing ML Training with Metagradient Descent </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Engstrom,+L">Logan Engstrom</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ilyas,+A">Andrew Ilyas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+B">Benjamin Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Feldmann,+A">Axel Feldmann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Moses,+W">William Moses</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Madry,+A">Aleksander Madry</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2503.13676" title="Abstract" id="2503.13676"> arXiv:2503.13676 </a> [<a href="/pdf/2503.13676" title="Download PDF" id="pdf-2503.13676" aria-labelledby="pdf-2503.13676">pdf</a>, <a href="https://arxiv.org/html/2503.13676v1" title="View HTML" id="html-2503.13676" aria-labelledby="html-2503.13676" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13676" title="Other formats" id="oth-2503.13676" aria-labelledby="oth-2503.13676">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Kernel Regression for Functional Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kusaba,+M">Minoru Kusaba</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Iwayama,+M">Megumi Iwayama</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yoshida,+R">Ryo Yoshida</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/2503.13562" title="Abstract" id="2503.13562"> arXiv:2503.13562 </a> [<a href="/pdf/2503.13562" title="Download PDF" id="pdf-2503.13562" aria-labelledby="pdf-2503.13562">pdf</a>, <a href="https://arxiv.org/html/2503.13562v1" title="View HTML" id="html-2503.13562" aria-labelledby="html-2503.13562" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13562" title="Other formats" id="oth-2503.13562" aria-labelledby="oth-2503.13562">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Micro Text Classification Based on Balanced Positive-Unlabeled Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Jia,+L">Lin-Han Jia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Guo,+L">Lan-Zhe Guo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhou,+Z">Zhi Zhou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Han,+S">Si-Ye Han</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Z">Zi-Wen Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Y">Yu-Feng Li</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/2503.13512" title="Abstract" id="2503.13512"> arXiv:2503.13512 </a> [<a href="/pdf/2503.13512" title="Download PDF" id="pdf-2503.13512" aria-labelledby="pdf-2503.13512">pdf</a>, <a href="https://arxiv.org/html/2503.13512v1" title="View HTML" id="html-2503.13512" aria-labelledby="html-2503.13512" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13512" title="Other formats" id="oth-2503.13512" aria-labelledby="oth-2503.13512">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Positivity sets of hinge functions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Schicho,+J">Josef Schicho</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tewari,+A+K">Ayush Kumar Tewari</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Warren,+A">Audie Warren</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Discrete Mathematics (cs.DM); Machine Learning (cs.LG); Symbolic Computation (cs.SC); Combinatorics (math.CO); Functional Analysis (math.FA) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2503.14403" title="Abstract" id="2503.14403"> arXiv:2503.14403 </a> (cross-list from cs.LG) [<a href="/pdf/2503.14403" title="Download PDF" id="pdf-2503.14403" aria-labelledby="pdf-2503.14403">pdf</a>, <a href="https://arxiv.org/html/2503.14403v1" title="View HTML" id="html-2503.14403" aria-labelledby="html-2503.14403" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14403" title="Other formats" id="oth-2503.14403" aria-labelledby="oth-2503.14403">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Landscape Complexity for the Empirical Risk of Generalized Linear Models: Discrimination between Structured Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tsironis,+T+G">Theodoros G. Tsironis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moustakas,+A+L">Aris L. Moustakas</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Statistical Mechanics (cond-mat.stat-mech); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2503.14297" title="Abstract" id="2503.14297"> arXiv:2503.14297 </a> (cross-list from cs.LG) [<a href="/pdf/2503.14297" title="Download PDF" id="pdf-2503.14297" aria-labelledby="pdf-2503.14297">pdf</a>, <a href="https://arxiv.org/html/2503.14297v1" title="View HTML" id="html-2503.14297" aria-labelledby="html-2503.14297" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14297" title="Other formats" id="oth-2503.14297" aria-labelledby="oth-2503.14297">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improved Scalable Lipschitz Bounds for Deep Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Syed,+U">Usman Syed</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+B">Bin Hu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Systems and Control (eess.SY); Optimization and Control (math.OC); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2503.14106" title="Abstract" id="2503.14106"> arXiv:2503.14106 </a> (cross-list from cs.CV) [<a href="/pdf/2503.14106" title="Download PDF" id="pdf-2503.14106" aria-labelledby="pdf-2503.14106">pdf</a>, <a href="https://arxiv.org/html/2503.14106v1" title="View HTML" id="html-2503.14106" aria-labelledby="html-2503.14106" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14106" title="Other formats" id="oth-2503.14106" aria-labelledby="oth-2503.14106">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jonkers,+J">Jef Jonkers</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Coopman,+F">Frank Coopman</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Duchateau,+L">Luc Duchateau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Van+Wallendael,+G">Glenn Van Wallendael</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Van+Hoecke,+S">Sofie Van Hoecke</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 33 pages, 10 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Vision and Pattern Recognition (cs.CV)</span>; Artificial Intelligence (cs.AI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2503.14009" title="Abstract" id="2503.14009"> arXiv:2503.14009 </a> (cross-list from q-bio.QM) [<a href="/pdf/2503.14009" title="Download PDF" id="pdf-2503.14009" aria-labelledby="pdf-2503.14009">pdf</a>, <a href="https://arxiv.org/html/2503.14009v1" title="View HTML" id="html-2503.14009" aria-labelledby="html-2503.14009" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.14009" title="Other formats" id="oth-2503.14009" aria-labelledby="oth-2503.14009">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study </div> <div class='list-authors'><a href="https://arxiv.org/search/q-bio?searchtype=author&query=Ghosh,+A">Adrita Ghosh</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Das,+P">Parthasakha Das</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Chakraborty,+T">Tanujit Chakraborty</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Das,+P">Pritha Das</a>, <a href="https://arxiv.org/search/q-bio?searchtype=author&query=Ghosh,+D">Dibakar Ghosh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantitative Methods (q-bio.QM)</span>; Dynamical Systems (math.DS); Chaotic Dynamics (nlin.CD); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/2503.13909" title="Abstract" id="2503.13909"> arXiv:2503.13909 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13909" title="Download PDF" id="pdf-2503.13909" aria-labelledby="pdf-2503.13909">pdf</a>, <a href="https://arxiv.org/html/2503.13909v1" title="View HTML" id="html-2503.13909" aria-labelledby="html-2503.13909" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13909" title="Other formats" id="oth-2503.13909" aria-labelledby="oth-2503.13909">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bera,+P">Pavia Bera</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bhanja,+S">Sanjukta Bhanja</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='item27'>[27]</a> <a href ="/abs/2503.13893" title="Abstract" id="2503.13893"> arXiv:2503.13893 </a> (cross-list from math.OC) [<a href="/pdf/2503.13893" title="Download PDF" id="pdf-2503.13893" aria-labelledby="pdf-2503.13893">pdf</a>, <a href="https://arxiv.org/html/2503.13893v1" title="View HTML" id="html-2503.13893" aria-labelledby="html-2503.13893" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13893" title="Other formats" id="oth-2503.13893" aria-labelledby="oth-2503.13893">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Relaxed Wasserstein Distance Formulation for Mixtures of Radially Contoured Distributions </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Chen,+K">Keyu Chen</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Wang,+Z">Zetian Wang</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Zhang,+Y">Yunxin Zhang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Optimization and Control (math.OC)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/2503.13842" title="Abstract" id="2503.13842"> arXiv:2503.13842 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13842" title="Download PDF" id="pdf-2503.13842" aria-labelledby="pdf-2503.13842">pdf</a>, <a href="https://arxiv.org/html/2503.13842v1" title="View HTML" id="html-2503.13842" aria-labelledby="html-2503.13842" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13842" title="Other formats" id="oth-2503.13842" aria-labelledby="oth-2503.13842">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Counterfactual experience augmented off-policy reinforcement learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+S">Sunbowen Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gong,+Y">Yicheng Gong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+C">Chao Deng</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by Neurocomputing, <a href="https://doi.org/10.1016/j.neucom.2025.130017" 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>; Artificial Intelligence (cs.AI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2503.13755" title="Abstract" id="2503.13755"> arXiv:2503.13755 </a> (cross-list from astro-ph.CO) [<a href="/pdf/2503.13755" title="Download PDF" id="pdf-2503.13755" aria-labelledby="pdf-2503.13755">pdf</a>, <a href="https://arxiv.org/html/2503.13755v1" title="View HTML" id="html-2503.13755" aria-labelledby="html-2503.13755" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13755" title="Other formats" id="oth-2503.13755" aria-labelledby="oth-2503.13755">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> How many simulations do we need for simulation-based inference in cosmology? </div> <div class='list-authors'><a href="https://arxiv.org/search/astro-ph?searchtype=author&query=Bairagi,+A">Anirban Bairagi</a>, <a href="https://arxiv.org/search/astro-ph?searchtype=author&query=Wandelt,+B">Benjamin Wandelt</a>, <a href="https://arxiv.org/search/astro-ph?searchtype=author&query=Villaescusa-Navarro,+F">Francisco Villaescusa-Navarro</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cosmology and Nongalactic Astrophysics (astro-ph.CO)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2503.13506" title="Abstract" id="2503.13506"> arXiv:2503.13506 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13506" title="Download PDF" id="pdf-2503.13506" aria-labelledby="pdf-2503.13506">pdf</a>, <a href="https://arxiv.org/html/2503.13506v1" title="View HTML" id="html-2503.13506" aria-labelledby="html-2503.13506" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13506" title="Other formats" id="oth-2503.13506" aria-labelledby="oth-2503.13506">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Role of Hyperparameters in Predictive Multiplicity </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Cavus,+M">Mustafa Cavus</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wo%C5%BAnica,+K">Katarzyna Wo藕nica</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Biecek,+P">Przemys艂aw Biecek</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 4 figures </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='item31'>[31]</a> <a href ="/abs/2503.13078" title="Abstract" id="2503.13078"> arXiv:2503.13078 </a> (cross-list from stat.ME) [<a href="/pdf/2503.13078" title="Download PDF" id="pdf-2503.13078" aria-labelledby="pdf-2503.13078">pdf</a>, <a href="https://arxiv.org/html/2503.13078v1" title="View HTML" id="html-2503.13078" aria-labelledby="html-2503.13078" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13078" title="Other formats" id="oth-2503.13078" aria-labelledby="oth-2503.13078">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hermansen,+T+%C3%98">Tobias 脴stmo Hermansen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zucknick,+M">Manuela Zucknick</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+Z">Zhi Zhao</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Genomics (q-bio.GN); Machine Learning (stat.ML) </div> </div> </dd> </dl> <dl id='articles'> <h3>Tue, 18 Mar 2025 (showing first 19 of 46 entries )</h3> <dt> <a name='item32'>[32]</a> <a href ="/abs/2503.13317" title="Abstract" id="2503.13317"> arXiv:2503.13317 </a> [<a href="/pdf/2503.13317" title="Download PDF" id="pdf-2503.13317" aria-labelledby="pdf-2503.13317">pdf</a>, <a href="https://arxiv.org/html/2503.13317v1" title="View HTML" id="html-2503.13317" aria-labelledby="html-2503.13317" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13317" title="Other formats" id="oth-2503.13317" aria-labelledby="oth-2503.13317">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Do you understand epistemic uncertainty? Think again! Rigorous frequentist epistemic uncertainty estimation in regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Foglia,+E">Enrico Foglia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bobbia,+B">Benjamin Bobbia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Durasov,+N">Nikita Durasov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bauerheim,+M">Michael Bauerheim</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fua,+P">Pascal Fua</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Moreau,+S">Stephane Moreau</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jardin,+T">Thierry Jardin</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2503.13050" title="Abstract" id="2503.13050"> arXiv:2503.13050 </a> [<a href="/pdf/2503.13050" title="Download PDF" id="pdf-2503.13050" aria-labelledby="pdf-2503.13050">pdf</a>, <a href="https://arxiv.org/html/2503.13050v2" title="View HTML" id="html-2503.13050" aria-labelledby="html-2503.13050" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13050" title="Other formats" id="oth-2503.13050" aria-labelledby="oth-2503.13050">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> E-Values Expand the Scope of Conformal Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gauthier,+E">Etienne Gauthier</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bach,+F">Francis Bach</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jordan,+M+I">Michael I. Jordan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Code available at: <a href="https://github.com/GauthierE/evalues-expand-cp" 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 (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/2503.12893" title="Abstract" id="2503.12893"> arXiv:2503.12893 </a> [<a href="/pdf/2503.12893" title="Download PDF" id="pdf-2503.12893" aria-labelledby="pdf-2503.12893">pdf</a>, <a href="https://arxiv.org/html/2503.12893v1" title="View HTML" id="html-2503.12893" aria-labelledby="html-2503.12893" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12893" title="Other formats" id="oth-2503.12893" aria-labelledby="oth-2503.12893">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Edgeworth Expansion for Semi-hard Triplet Loss </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kimura,+M">Masanari Kimura</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2503.12808" title="Abstract" id="2503.12808"> arXiv:2503.12808 </a> [<a href="/pdf/2503.12808" title="Download PDF" id="pdf-2503.12808" aria-labelledby="pdf-2503.12808">pdf</a>, <a href="https://arxiv.org/html/2503.12808v2" title="View HTML" id="html-2503.12808" aria-labelledby="html-2503.12808" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12808" title="Other formats" id="oth-2503.12808" aria-labelledby="oth-2503.12808">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Estimating stationary mass, frequency by frequency </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Nakul,+M">Milind Nakul</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Muthukumar,+V">Vidya Muthukumar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pananjady,+A">Ashwin Pananjady</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Information Theory (cs.IT); Machine Learning (cs.LG); Probability (math.PR); Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2503.12760" title="Abstract" id="2503.12760"> arXiv:2503.12760 </a> [<a href="/pdf/2503.12760" title="Download PDF" id="pdf-2503.12760" aria-labelledby="pdf-2503.12760">pdf</a>, <a href="https://arxiv.org/html/2503.12760v1" title="View HTML" id="html-2503.12760" aria-labelledby="html-2503.12760" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12760" title="Other formats" id="oth-2503.12760" aria-labelledby="oth-2503.12760">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SNPL: Simultaneous Policy Learning and Evaluation for Safe Multi-Objective Policy Improvement </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Cho,+B">Brian Cho</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pop,+A">Ana-Roxana Pop</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Evince,+A">Ariel Evince</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kallus,+N">Nathan Kallus</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Econometrics (econ.EM) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2503.12456" title="Abstract" id="2503.12456"> arXiv:2503.12456 </a> [<a href="/pdf/2503.12456" title="Download PDF" id="pdf-2503.12456" aria-labelledby="pdf-2503.12456">pdf</a>, <a href="https://arxiv.org/html/2503.12456v1" title="View HTML" id="html-2503.12456" aria-labelledby="html-2503.12456" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12456" title="Other formats" id="oth-2503.12456" aria-labelledby="oth-2503.12456">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonlinear Principal Component Analysis with Random Bernoulli Features for Process Monitoring </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+K">Ke Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jiang,+D">Dandan Jiang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Applications (stat.AP); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2503.12266" title="Abstract" id="2503.12266"> arXiv:2503.12266 </a> [<a href="/pdf/2503.12266" title="Download PDF" id="pdf-2503.12266" aria-labelledby="pdf-2503.12266">pdf</a>, <a href="https://arxiv.org/html/2503.12266v1" title="View HTML" id="html-2503.12266" aria-labelledby="html-2503.12266" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12266" title="Other formats" id="oth-2503.12266" aria-labelledby="oth-2503.12266">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Support Collapse of Deep Gaussian Processes with Polynomial Kernels for a Wide Regime of Hyperparameters </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chernobrovkina,+D">Daryna Chernobrovkina</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gr%C3%BCnew%C3%A4lder,+S">Steffen Gr眉new盲lder</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2503.11854" title="Abstract" id="2503.11854"> arXiv:2503.11854 </a> [<a href="/pdf/2503.11854" title="Download PDF" id="pdf-2503.11854" aria-labelledby="pdf-2503.11854">pdf</a>, <a href="https://arxiv.org/html/2503.11854v1" title="View HTML" id="html-2503.11854" aria-labelledby="html-2503.11854" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.11854" title="Other formats" id="oth-2503.11854" aria-labelledby="oth-2503.11854">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayes and Biased Estimators Without Hyper-parameter Estimation: Comparable Performance to the Empirical-Bayes-Based Regularized Estimator </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ju,+Y">Yue Ju</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wahlberg,+B">Bo Wahlberg</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hjalmarsson,+H">H氓kan Hjalmarsson</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Systems and Control (eess.SY) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/2503.11773" title="Abstract" id="2503.11773"> arXiv:2503.11773 </a> [<a href="/pdf/2503.11773" title="Download PDF" id="pdf-2503.11773" aria-labelledby="pdf-2503.11773">pdf</a>, <a href="https://arxiv.org/html/2503.11773v1" title="View HTML" id="html-2503.11773" aria-labelledby="html-2503.11773" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.11773" title="Other formats" id="oth-2503.11773" aria-labelledby="oth-2503.11773">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Ranking and Selection with Simultaneous Input Data Collection </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yuhao Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhou,+E">Enlu Zhou</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/2503.13404" title="Abstract" id="2503.13404"> arXiv:2503.13404 </a> (cross-list from cs.AI) [<a href="/pdf/2503.13404" title="Download PDF" id="pdf-2503.13404" aria-labelledby="pdf-2503.13404">pdf</a>, <a href="https://arxiv.org/html/2503.13404v1" title="View HTML" id="html-2503.13404" aria-labelledby="html-2503.13404" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13404" title="Other formats" id="oth-2503.13404" aria-labelledby="oth-2503.13404">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jeong,+C">Cheoljoon Jeong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yue,+X">Xubo Yue</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chung,+S">Seokhyun Chung</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Artificial Intelligence (cs.AI)</span>; Machine Learning (cs.LG); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2503.13366" title="Abstract" id="2503.13366"> arXiv:2503.13366 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13366" title="Download PDF" id="pdf-2503.13366" aria-labelledby="pdf-2503.13366">pdf</a>, <a href="https://arxiv.org/html/2503.13366v1" title="View HTML" id="html-2503.13366" aria-labelledby="html-2503.13366" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13366" title="Other formats" id="oth-2503.13366" aria-labelledby="oth-2503.13366">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Follow-the-Regularized-Leader with Adversarial Constraints </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ferreira,+R+N">Ricardo N. Ferreira</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Soares,+C">Cl谩udia Soares</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Data Structures and Algorithms (cs.DS); Optimization and Control (math.OC); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2503.13296" title="Abstract" id="2503.13296"> arXiv:2503.13296 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13296" title="Download PDF" id="pdf-2503.13296" aria-labelledby="pdf-2503.13296">pdf</a>, <a href="https://arxiv.org/html/2503.13296v1" title="View HTML" id="html-2503.13296" aria-labelledby="html-2503.13296" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13296" title="Other formats" id="oth-2503.13296" aria-labelledby="oth-2503.13296">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Local Posterior Structure in Deep Ensembles </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jordahn,+M">Mikkel Jordahn</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jensen,+J+V">Jonas Vestergaard Jensen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schmidt,+M+N">Mikkel N. Schmidt</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Andersen,+M+R">Michael Riis Andersen</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Code and models available at <a href="https://github.com/jonasvj/OnLocalPosteriorStructureInDeepEnsembles" 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>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/2503.13115" title="Abstract" id="2503.13115"> arXiv:2503.13115 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13115" title="Download PDF" id="pdf-2503.13115" aria-labelledby="pdf-2503.13115">pdf</a>, <a href="/format/2503.13115" title="Other formats" id="oth-2503.13115" aria-labelledby="oth-2503.13115">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tankala,+C">Chandan Tankala</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nagaraj,+D+M">Dheeraj M. Nagaraj</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Raj,+A">Anant Raj</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Probability (math.PR); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/2503.13051" title="Abstract" id="2503.13051"> arXiv:2503.13051 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13051" title="Download PDF" id="pdf-2503.13051" aria-labelledby="pdf-2503.13051">pdf</a>, <a href="https://arxiv.org/html/2503.13051v1" title="View HTML" id="html-2503.13051" aria-labelledby="html-2503.13051" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13051" title="Other formats" id="oth-2503.13051" aria-labelledby="oth-2503.13051">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Permutation Learning with Only N Parameters: From SoftSort to Self-Organizing Gaussians </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Barthel,+K+U">Kai Uwe Barthel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Barthel,+F">Florian Barthel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Eisert,+P">Peter Eisert</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); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/2503.13037" title="Abstract" id="2503.13037"> arXiv:2503.13037 </a> (cross-list from stat.ME) [<a href="/pdf/2503.13037" title="Download PDF" id="pdf-2503.13037" aria-labelledby="pdf-2503.13037">pdf</a>, <a href="https://arxiv.org/html/2503.13037v1" title="View HTML" id="html-2503.13037" aria-labelledby="html-2503.13037" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13037" title="Other formats" id="oth-2503.13037" aria-labelledby="oth-2503.13037">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> H-AddiVortes: Heteroscedastic (Bayesian) Additive Voronoi Tessellations </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Stone,+A+J">Adam J. Stone</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gosling,+J+P">John Paul Gosling</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 7 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Computation (stat.CO); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/2503.13001" title="Abstract" id="2503.13001"> arXiv:2503.13001 </a> (cross-list from cs.LG) [<a href="/pdf/2503.13001" title="Download PDF" id="pdf-2503.13001" aria-labelledby="pdf-2503.13001">pdf</a>, <a href="https://arxiv.org/html/2503.13001v1" title="View HTML" id="html-2503.13001" aria-labelledby="html-2503.13001" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.13001" title="Other formats" id="oth-2503.13001" aria-labelledby="oth-2503.13001">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Linear-Size Neural Network Representation of Piecewise Affine Functions in $\mathbb{R}^2$ </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zanotti,+L">Leo Zanotti</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Neural and Evolutionary Computing (cs.NE); Metric Geometry (math.MG); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/2503.12966" title="Abstract" id="2503.12966"> arXiv:2503.12966 </a> (cross-list from cs.LG) [<a href="/pdf/2503.12966" title="Download PDF" id="pdf-2503.12966" aria-labelledby="pdf-2503.12966">pdf</a>, <a href="/format/2503.12966" title="Other formats" id="oth-2503.12966" aria-labelledby="oth-2503.12966">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Beyler,+E">Eliot Beyler</a> (SIERRA), <a href="https://arxiv.org/search/cs?searchtype=author&query=Bach,+F">Francis Bach</a> (SIERRA)</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='item49'>[49]</a> <a href ="/abs/2503.12930" title="Abstract" id="2503.12930"> arXiv:2503.12930 </a> (cross-list from cs.LG) [<a href="/pdf/2503.12930" title="Download PDF" id="pdf-2503.12930" aria-labelledby="pdf-2503.12930">pdf</a>, <a href="/format/2503.12930" title="Other formats" id="oth-2503.12930" aria-labelledby="oth-2503.12930">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Augmented Invertible Koopman Autoencoder for long-term time series forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Frion,+A">Anthony Frion</a> (Lab-STICC_OSE, IMT Atlantique - MEE), <a href="https://arxiv.org/search/cs?searchtype=author&query=Drumetz,+L">Lucas Drumetz</a> (IMT Atlantique - MEE, Lab-STICC_OSE), <a href="https://arxiv.org/search/cs?searchtype=author&query=Mura,+M+D">Mauro Dalla Mura</a> (GIPSA-SIGMAPHY), <a href="https://arxiv.org/search/cs?searchtype=author&query=Tochon,+G">Guillaume Tochon</a> (GIPSA-SIGMAPHY), <a href="https://arxiv.org/search/cs?searchtype=author&query=A%C3%AFssa-El-Bey,+A">Abdeldjalil A茂ssa-El-Bey</a> (IMT Atlantique - MEE, Lab-STICC_COSYDE)</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='item50'>[50]</a> <a href ="/abs/2503.12822" title="Abstract" id="2503.12822"> arXiv:2503.12822 </a> (cross-list from cs.LG) [<a href="/pdf/2503.12822" title="Download PDF" id="pdf-2503.12822" aria-labelledby="pdf-2503.12822">pdf</a>, <a href="https://arxiv.org/html/2503.12822v1" title="View HTML" id="html-2503.12822" aria-labelledby="html-2503.12822" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.12822" title="Other formats" id="oth-2503.12822" aria-labelledby="oth-2503.12822">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Optimization Framework for Differentially Private Sparse Fine-Tuning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Makni,+M">Mehdi Makni</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Behdin,+K">Kayhan Behdin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Afriat,+G">Gabriel Afriat</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+Z">Zheng Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vassilvitskii,+S">Sergei Vassilvitskii</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ponomareva,+N">Natalia Ponomareva</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hazimeh,+H">Hussein Hazimeh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mazumder,+R">Rahul Mazumder</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; 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