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href="/list/cs.LG/recent?skip=135&show=50"> Tue, 26 Nov 2024 </a> </li><li> <a href="/list/cs.LG/recent?skip=383&show=50"> Mon, 25 Nov 2024 </a> </li><li> <a href="/list/cs.LG/recent?skip=520&show=50"> Fri, 22 Nov 2024 </a> </li><li> <a href="/list/cs.LG/recent?skip=633&show=50"> Thu, 21 Nov 2024 </a> </li></ul> <p>See today's <a id="new-cs.LG" aria-labelledby="new-cs.LG" href="/list/cs.LG/new">new</a> changes</p> <div class='paging'>Total of 733 entries : <span>1-50</span> <a href=/list/cs.LG/recent?skip=50&show=50>51-100</a> <a href=/list/cs.LG/recent?skip=100&show=50>101-150</a> <a href=/list/cs.LG/recent?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/recent?skip=700&show=50>701-733</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/recent?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/recent?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/recent?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <h3>Wed, 27 Nov 2024 (showing first 50 of 135 entries )</h3> <dt> <a name='item1'>[1]</a> <a href ="/abs/2411.17691" title="Abstract" id="2411.17691"> arXiv:2411.17691 </a> [<a href="/pdf/2411.17691" title="Download PDF" id="pdf-2411.17691" aria-labelledby="pdf-2411.17691">pdf</a>, <a href="https://arxiv.org/html/2411.17691v1" title="View HTML" id="html-2411.17691" aria-labelledby="html-2411.17691" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17691" title="Other formats" id="oth-2411.17691" aria-labelledby="oth-2411.17691">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ouyang,+X">Xu Ouyang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ge,+T">Tao Ge</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hartvigsen,+T">Thomas Hartvigsen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Z">Zhisong Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mi,+H">Haitao Mi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+D">Dong Yu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Work in progress; Please note that Figure 1's gray areas may not be displayed properly using Chrome (maybe due to bugs in Chrome) </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='item2'>[2]</a> <a href ="/abs/2411.17685" title="Abstract" id="2411.17685"> arXiv:2411.17685 </a> [<a href="/pdf/2411.17685" title="Download PDF" id="pdf-2411.17685" aria-labelledby="pdf-2411.17685">pdf</a>, <a href="https://arxiv.org/html/2411.17685v1" title="View HTML" id="html-2411.17685" aria-labelledby="html-2411.17685" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17685" title="Other formats" id="oth-2411.17685" aria-labelledby="oth-2411.17685">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Attamba: Attending To Multi-Token States </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Akhauri,+Y">Yash Akhauri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huda,+S">Safeen Huda</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Abdelfattah,+M+S">Mohamed S. Abdelfattah</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='item3'>[3]</a> <a href ="/abs/2411.17676" title="Abstract" id="2411.17676"> arXiv:2411.17676 </a> [<a href="/pdf/2411.17676" title="Download PDF" id="pdf-2411.17676" aria-labelledby="pdf-2411.17676">pdf</a>, <a href="https://arxiv.org/html/2411.17676v1" title="View HTML" id="html-2411.17676" aria-labelledby="html-2411.17676" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17676" title="Other formats" id="oth-2411.17676" aria-labelledby="oth-2411.17676">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Instance-Aware Graph Prompt Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jiazheng Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jundong Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+C">Chuxu Zhang</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='item4'>[4]</a> <a href ="/abs/2411.17672" title="Abstract" id="2411.17672"> arXiv:2411.17672 </a> [<a href="/pdf/2411.17672" title="Download PDF" id="pdf-2411.17672" aria-labelledby="pdf-2411.17672">pdf</a>, <a href="https://arxiv.org/html/2411.17672v1" title="View HTML" id="html-2411.17672" aria-labelledby="html-2411.17672" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17672" title="Other formats" id="oth-2411.17672" aria-labelledby="oth-2411.17672">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Synthetic Data Generation with LLM for Improved Depression Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kang,+A">Andrea Kang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J+Y">Jun Yu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee-Youngzie,+Z">Zoe Lee-Youngzie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fu,+S">Shuhao Fu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 6 pages excluding references and appendix </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='item5'>[5]</a> <a href ="/abs/2411.17668" title="Abstract" id="2411.17668"> arXiv:2411.17668 </a> [<a href="/pdf/2411.17668" title="Download PDF" id="pdf-2411.17668" aria-labelledby="pdf-2411.17668">pdf</a>, <a href="https://arxiv.org/html/2411.17668v1" title="View HTML" id="html-2411.17668" aria-labelledby="html-2411.17668" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17668" title="Other formats" id="oth-2411.17668" aria-labelledby="oth-2411.17668">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Anytime Acceleration of Gradient Descent </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Z">Zihan Zhang</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=Du,+S+S">Simon S. Du</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Y">Yuxin Chen</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='item6'>[6]</a> <a href ="/abs/2411.17645" title="Abstract" id="2411.17645"> arXiv:2411.17645 </a> [<a href="/pdf/2411.17645" title="Download PDF" id="pdf-2411.17645" aria-labelledby="pdf-2411.17645">pdf</a>, <a href="https://arxiv.org/html/2411.17645v1" title="View HTML" id="html-2411.17645" aria-labelledby="html-2411.17645" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17645" title="Other formats" id="oth-2411.17645" aria-labelledby="oth-2411.17645">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Explainable AI for Classifying UTI Risk Groups Using a Real-World Linked EHR and Pathology Lab Dataset </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dai,+Y">Yujie Dai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sullivan,+B">Brian Sullivan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Montout,+A">Axel Montout</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dillon,+A">Amy Dillon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Waller,+C">Chris Waller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Acs,+P">Peter Acs</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Denholm,+R">Rachel Denholm</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Williams,+P">Philip Williams</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hay,+A+D">Alastair D Hay</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Santos-Rodriguez,+R">Raul Santos-Rodriguez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dowsey,+A">Andrew Dowsey</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='item7'>[7]</a> <a href ="/abs/2411.17629" title="Abstract" id="2411.17629"> arXiv:2411.17629 </a> [<a href="/pdf/2411.17629" title="Download PDF" id="pdf-2411.17629" aria-labelledby="pdf-2411.17629">pdf</a>, <a href="https://arxiv.org/html/2411.17629v1" title="View HTML" id="html-2411.17629" aria-labelledby="html-2411.17629" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17629" title="Other formats" id="oth-2411.17629" aria-labelledby="oth-2411.17629">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Chemical Reaction Representation with Reactant-Product Alignment </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zeng,+K">Kaipeng Zeng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+X">Xianbin Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yu Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+X">Xiaokang Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jin,+Y">Yaohui Jin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+Y">Yanyan 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='item8'>[8]</a> <a href ="/abs/2411.17625" title="Abstract" id="2411.17625"> arXiv:2411.17625 </a> [<a href="/pdf/2411.17625" title="Download PDF" id="pdf-2411.17625" aria-labelledby="pdf-2411.17625">pdf</a>, <a href="/format/2411.17625" title="Other formats" id="oth-2411.17625" aria-labelledby="oth-2411.17625">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Data-driven development of cycle prediction models for lithium metal batteries using multi modal mining </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+J">Jaewoong Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Woo,+J">Junhee Woo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+S">Sejin Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Paulina,+C">Cinthya Paulina</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Park,+H">Hyunmin Park</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+H">Hee-Tak Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Park,+S">Steve Park</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+J">Jihan Kim</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 30 pages, 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='item9'>[9]</a> <a href ="/abs/2411.17624" title="Abstract" id="2411.17624"> arXiv:2411.17624 </a> [<a href="/pdf/2411.17624" title="Download PDF" id="pdf-2411.17624" aria-labelledby="pdf-2411.17624">pdf</a>, <a href="https://arxiv.org/html/2411.17624v1" title="View HTML" id="html-2411.17624" aria-labelledby="html-2411.17624" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17624" title="Other formats" id="oth-2411.17624" aria-labelledby="oth-2411.17624">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Machine Learning and Multi-source Remote Sensing in Forest Carbon Stock Estimation: A Review </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Nguyen,+A">Autumn Nguyen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saha,+S">Sulagna Saha</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> First author and corresponding author: Autumn Nguyen </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/2411.17595" title="Abstract" id="2411.17595"> arXiv:2411.17595 </a> [<a href="/pdf/2411.17595" title="Download PDF" id="pdf-2411.17595" aria-labelledby="pdf-2411.17595">pdf</a>, <a href="https://arxiv.org/html/2411.17595v1" title="View HTML" id="html-2411.17595" aria-labelledby="html-2411.17595" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17595" title="Other formats" id="oth-2411.17595" aria-labelledby="oth-2411.17595">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Can artificial intelligence predict clinical trial outcomes? </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jin,+S">Shuyi Jin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+L">Lu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ding,+H">Hongru Ding</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+M">Meijie Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+L">Lun Yu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2411.17582" title="Abstract" id="2411.17582"> arXiv:2411.17582 </a> [<a href="/pdf/2411.17582" title="Download PDF" id="pdf-2411.17582" aria-labelledby="pdf-2411.17582">pdf</a>, <a href="https://arxiv.org/html/2411.17582v1" title="View HTML" id="html-2411.17582" aria-labelledby="html-2411.17582" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17582" title="Other formats" id="oth-2411.17582" aria-labelledby="oth-2411.17582">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Fairness to Infinity: Outcome-Indistinguishable (Omni)Prediction in Evolving Graphs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dwork,+C">Cynthia Dwork</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hays,+C">Chris Hays</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Immorlica,+N">Nicole Immorlica</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Perdomo,+J+C">Juan C. Perdomo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tankala,+P">Pranay Tankala</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computers and Society (cs.CY); Social and Information Networks (cs.SI) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2411.17570" title="Abstract" id="2411.17570"> arXiv:2411.17570 </a> [<a href="/pdf/2411.17570" title="Download PDF" id="pdf-2411.17570" aria-labelledby="pdf-2411.17570">pdf</a>, <a href="https://arxiv.org/html/2411.17570v1" title="View HTML" id="html-2411.17570" aria-labelledby="html-2411.17570" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17570" title="Other formats" id="oth-2411.17570" aria-labelledby="oth-2411.17570">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ferstad,+J+O">Johannes O. Ferstad</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fox,+E+B">Emily B. Fox</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Scheinker,+D">David Scheinker</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Johari,+R">Ramesh Johari</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Proceedings of Machine Learning for Health (ML4H) 2024. Code available at: <a href="https://github.com/jferstad/ml4h-explainable-policies" 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); Applications (stat.AP); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2411.17555" title="Abstract" id="2411.17555"> arXiv:2411.17555 </a> [<a href="/pdf/2411.17555" title="Download PDF" id="pdf-2411.17555" aria-labelledby="pdf-2411.17555">pdf</a>, <a href="/format/2411.17555" title="Other formats" id="oth-2411.17555" aria-labelledby="oth-2411.17555">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multiscale spatiotemporal heterogeneity analysis of bike-sharing system's self-loop phenomenon: Evidence from Shanghai </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yichen Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+Q">Qing Yu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+Y">Yancun Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yuan,+Q">Quan Yuan</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=Yu,+C">Chengcheng Yu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2411.17554" title="Abstract" id="2411.17554"> arXiv:2411.17554 </a> [<a href="/pdf/2411.17554" title="Download PDF" id="pdf-2411.17554" aria-labelledby="pdf-2411.17554">pdf</a>, <a href="/format/2411.17554" title="Other formats" id="oth-2411.17554" aria-labelledby="oth-2411.17554">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Navigating Spatial Inequities in Freight Truck Crash Severity via Counterfactual Inference in Los Angeles </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yichen Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yin,+H">Hao Yin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yifan Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+C">Chenyang Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+S">Siqin Wang</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='item15'>[15]</a> <a href ="/abs/2411.17528" title="Abstract" id="2411.17528"> arXiv:2411.17528 </a> [<a href="/pdf/2411.17528" title="Download PDF" id="pdf-2411.17528" aria-labelledby="pdf-2411.17528">pdf</a>, <a href="/format/2411.17528" title="Other formats" id="oth-2411.17528" aria-labelledby="oth-2411.17528">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Evolving Markov Chains: Unsupervised Mode Discovery and Recognition from Data Streams </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Co%C5%9Fkun,+K">Kutalm谋艧 Co艧kun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=T%C3%BCmer,+B">Borahan T眉mer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hiller,+B+C">Bjarne C. Hiller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Becker,+M">Martin Becker</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 20 pages, 8 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='item16'>[16]</a> <a href ="/abs/2411.17525" title="Abstract" id="2411.17525"> arXiv:2411.17525 </a> [<a href="/pdf/2411.17525" title="Download PDF" id="pdf-2411.17525" aria-labelledby="pdf-2411.17525">pdf</a>, <a href="https://arxiv.org/html/2411.17525v1" title="View HTML" id="html-2411.17525" aria-labelledby="html-2411.17525" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17525" title="Other formats" id="oth-2411.17525" aria-labelledby="oth-2411.17525">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Pushing the Limits of Large Language Model Quantization via the Linearity Theorem </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Malinovskii,+V">Vladimir Malinovskii</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Panferov,+A">Andrei Panferov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ilin,+I">Ivan Ilin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+H">Han Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Richt%C3%A1rik,+P">Peter Richt谩rik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Alistarh,+D">Dan Alistarh</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='item17'>[17]</a> <a href ="/abs/2411.17511" title="Abstract" id="2411.17511"> arXiv:2411.17511 </a> [<a href="/pdf/2411.17511" title="Download PDF" id="pdf-2411.17511" aria-labelledby="pdf-2411.17511">pdf</a>, <a href="https://arxiv.org/html/2411.17511v1" title="View HTML" id="html-2411.17511" aria-labelledby="html-2411.17511" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17511" title="Other formats" id="oth-2411.17511" aria-labelledby="oth-2411.17511">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Training Hamiltonian neural networks without backpropagation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Rahma,+A">Atamert Rahma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Datar,+C">Chinmay Datar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dietrich,+F">Felix Dietrich</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 2 figures and 2 tables in the main text, includes an Appendix section, accepted to NeurIPS 2024 Workshop ML4PS </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='item18'>[18]</a> <a href ="/abs/2411.17506" title="Abstract" id="2411.17506"> arXiv:2411.17506 </a> [<a href="/pdf/2411.17506" title="Download PDF" id="pdf-2411.17506" aria-labelledby="pdf-2411.17506">pdf</a>, <a href="/format/2411.17506" title="Other formats" id="oth-2411.17506" aria-labelledby="oth-2411.17506">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural network modelling of kinematic and dynamic features for signature verification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Diaz,+M">Moises Diaz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ferrer,+M+A">Miguel A. Ferrer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Quintana,+J+J">Jose Juan Quintana</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wolniakowski,+A">Adam Wolniakowski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Trochimczuk,+R">Roman Trochimczuk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Miatliuk,+K">Konstantsin Miatliuk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Castellano,+G">Giovanna Castellano</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vessio,+G">Gennaro Vessio</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Procedia Computer Science, Volume 3, 2011, Pages 155-161 </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='item19'>[19]</a> <a href ="/abs/2411.17502" title="Abstract" id="2411.17502"> arXiv:2411.17502 </a> [<a href="/pdf/2411.17502" title="Download PDF" id="pdf-2411.17502" aria-labelledby="pdf-2411.17502">pdf</a>, <a href="https://arxiv.org/html/2411.17502v1" title="View HTML" id="html-2411.17502" aria-labelledby="html-2411.17502" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17502" title="Other formats" id="oth-2411.17502" aria-labelledby="oth-2411.17502">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bruys,+T">Thomas Bruys</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zandehshahvar,+R">Reza Zandehshahvar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hijazi,+A">Amira Hijazi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Van+Hentenryck,+P">Pascal Van Hentenryck</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 11 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='item20'>[20]</a> <a href ="/abs/2411.17501" title="Abstract" id="2411.17501"> arXiv:2411.17501 </a> [<a href="/pdf/2411.17501" title="Download PDF" id="pdf-2411.17501" aria-labelledby="pdf-2411.17501">pdf</a>, <a href="https://arxiv.org/html/2411.17501v1" title="View HTML" id="html-2411.17501" aria-labelledby="html-2411.17501" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17501" title="Other formats" id="oth-2411.17501" aria-labelledby="oth-2411.17501">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Inference Scaling $\scriptsize\mathtt{F}$Laws: The Limits of LLM Resampling with Imperfect Verifiers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Stroebl,+B">Benedikt Stroebl</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kapoor,+S">Sayash Kapoor</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Narayanan,+A">Arvind Narayanan</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='item21'>[21]</a> <a href ="/abs/2411.17499" title="Abstract" id="2411.17499"> arXiv:2411.17499 </a> [<a href="/pdf/2411.17499" title="Download PDF" id="pdf-2411.17499" aria-labelledby="pdf-2411.17499">pdf</a>, <a href="/format/2411.17499" title="Other formats" id="oth-2411.17499" aria-labelledby="oth-2411.17499">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Time-Series Forecasting in Smart Manufacturing Systems: An Experimental Evaluation of the State-of-the-art Algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Farahani,+M+A">Mojtaba A. Farahani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kalach,+F+E">Fadi El Kalach</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Harper,+A">Austin Harper</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=McCormick,+M+R">M. R. McCormick</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Harik,+R">Ramy Harik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wuest,+T">Thorsten Wuest</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='item22'>[22]</a> <a href ="/abs/2411.17471" title="Abstract" id="2411.17471"> arXiv:2411.17471 </a> [<a href="/pdf/2411.17471" title="Download PDF" id="pdf-2411.17471" aria-labelledby="pdf-2411.17471">pdf</a>, <a href="https://arxiv.org/html/2411.17471v1" title="View HTML" id="html-2411.17471" aria-labelledby="html-2411.17471" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17471" title="Other formats" id="oth-2411.17471" aria-labelledby="oth-2411.17471">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning New Concepts, Remembering the Old: A Novel Continual Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lai,+S">Songning Lai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liao,+M">Mingqian Liao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+Z">Zhangyi Hu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+J">Jiayu Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+W">Wenshuo Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yue,+Y">Yutao Yue</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); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2411.17461" title="Abstract" id="2411.17461"> arXiv:2411.17461 </a> [<a href="/pdf/2411.17461" title="Download PDF" id="pdf-2411.17461" aria-labelledby="pdf-2411.17461">pdf</a>, <a href="/format/2411.17461" title="Other formats" id="oth-2411.17461" aria-labelledby="oth-2411.17461">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SoK: Decentralized AI (DeAI) </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Z">Zhipeng Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+R">Rui Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lui,+E">Elizabeth Lui</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shah,+V">Vatsal Shah</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiong,+X">Xihan Xiong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+J">Jiahao Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Crapis,+D">Davide Crapis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Knottenbelt,+W">William Knottenbelt</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This is a Systematization of Knowledge (SoK) for the rapidly evolving field of Decentralized AI (DeAI). We welcome valuable comments, suggestions, and collaboration to further refine and enhance this work. We hope our contribution will help accelerate the advancement of DeAI </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2411.17450" title="Abstract" id="2411.17450"> arXiv:2411.17450 </a> [<a href="/pdf/2411.17450" title="Download PDF" id="pdf-2411.17450" aria-labelledby="pdf-2411.17450">pdf</a>, <a href="https://arxiv.org/html/2411.17450v1" title="View HTML" id="html-2411.17450" aria-labelledby="html-2411.17450" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17450" title="Other formats" id="oth-2411.17450" aria-labelledby="oth-2411.17450">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Graph Neural Network deep-dive into successful counterattacks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bekkers,+J">Joris Bekkers</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sahasrabudhe,+A">Amod Sahasrabudhe</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages, 11 figures, first submitted (and accepted) at MIT Sloan Sports Analytics Conference 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Social and Information Networks (cs.SI) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2411.17444" title="Abstract" id="2411.17444"> arXiv:2411.17444 </a> [<a href="/pdf/2411.17444" title="Download PDF" id="pdf-2411.17444" aria-labelledby="pdf-2411.17444">pdf</a>, <a href="https://arxiv.org/html/2411.17444v1" title="View HTML" id="html-2411.17444" aria-labelledby="html-2411.17444" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17444" title="Other formats" id="oth-2411.17444" aria-labelledby="oth-2411.17444">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Maximally Separated Active Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kasarla,+T">Tejaswi Kasarla</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jha,+A">Abhishek Jha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tervoort,+F">Faye Tervoort</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cucchiara,+R">Rita Cucchiara</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mettes,+P">Pascal Mettes</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ECCV 2024 Beyond Euclidean Workshop (proceedings) </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='item26'>[26]</a> <a href ="/abs/2411.17429" title="Abstract" id="2411.17429"> arXiv:2411.17429 </a> [<a href="/pdf/2411.17429" title="Download PDF" id="pdf-2411.17429" aria-labelledby="pdf-2411.17429">pdf</a>, <a href="https://arxiv.org/html/2411.17429v1" title="View HTML" id="html-2411.17429" aria-labelledby="html-2411.17429" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17429" title="Other formats" id="oth-2411.17429" aria-labelledby="oth-2411.17429">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Rewiring Techniques to Mitigate Oversquashing and Oversmoothing in GNNs: A Survey </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Attali,+H">Hugo Attali</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Buscaldi,+D">Davide Buscaldi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pernelle,+N">Nathalie Pernelle</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='item27'>[27]</a> <a href ="/abs/2411.17426" title="Abstract" id="2411.17426"> arXiv:2411.17426 </a> [<a href="/pdf/2411.17426" title="Download PDF" id="pdf-2411.17426" aria-labelledby="pdf-2411.17426">pdf</a>, <a href="https://arxiv.org/html/2411.17426v1" title="View HTML" id="html-2411.17426" aria-labelledby="html-2411.17426" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17426" title="Other formats" id="oth-2411.17426" aria-labelledby="oth-2411.17426">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> CLOVER: Constrained Learning with Orthonormal Vectors for Eliminating Redundancy </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Meng,+F">Fanxu Meng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+M">Muhan Zhang</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='item28'>[28]</a> <a href ="/abs/2411.17387" title="Abstract" id="2411.17387"> arXiv:2411.17387 </a> [<a href="/pdf/2411.17387" title="Download PDF" id="pdf-2411.17387" aria-labelledby="pdf-2411.17387">pdf</a>, <a href="https://arxiv.org/html/2411.17387v1" title="View HTML" id="html-2411.17387" aria-labelledby="html-2411.17387" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17387" title="Other formats" id="oth-2411.17387" aria-labelledby="oth-2411.17387">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robust Bayesian Optimization via Localized Online Conformal Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+D">Dongwon Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zecchin,+M">Matteo Zecchin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Park,+S">Sangwoo Park</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kang,+J">Joonhyuk Kang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Simeone,+O">Osvaldo Simeone</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2411.17382" title="Abstract" id="2411.17382"> arXiv:2411.17382 </a> [<a href="/pdf/2411.17382" title="Download PDF" id="pdf-2411.17382" aria-labelledby="pdf-2411.17382">pdf</a>, <a href="https://arxiv.org/html/2411.17382v1" title="View HTML" id="html-2411.17382" aria-labelledby="html-2411.17382" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17382" title="Other formats" id="oth-2411.17382" aria-labelledby="oth-2411.17382">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MFF-FTNet: Multi-scale Feature Fusion across Frequency and Temporal Domains for Time Series Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shi,+Y">Yangyang Shi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+Q">Qianqian Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yong Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+J">Jianguo Sun</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='item30'>[30]</a> <a href ="/abs/2411.17372" title="Abstract" id="2411.17372"> arXiv:2411.17372 </a> [<a href="/pdf/2411.17372" title="Download PDF" id="pdf-2411.17372" aria-labelledby="pdf-2411.17372">pdf</a>, <a href="https://arxiv.org/html/2411.17372v1" title="View HTML" id="html-2411.17372" aria-labelledby="html-2411.17372" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17372" title="Other formats" id="oth-2411.17372" aria-labelledby="oth-2411.17372">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+Y">Yufan Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+W">Wei Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+A">Alexander Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hung,+N+Q+V">Nguyen Quoc Viet Hung</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhan,+C">Choujun Zhan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+T">Tong Chen</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 14 pages, 6 figures, 3 tables </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='item31'>[31]</a> <a href ="/abs/2411.17353" title="Abstract" id="2411.17353"> arXiv:2411.17353 </a> [<a href="/pdf/2411.17353" title="Download PDF" id="pdf-2411.17353" aria-labelledby="pdf-2411.17353">pdf</a>, <a href="https://arxiv.org/html/2411.17353v1" title="View HTML" id="html-2411.17353" aria-labelledby="html-2411.17353" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17353" title="Other formats" id="oth-2411.17353" aria-labelledby="oth-2411.17353">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Salahshour,+M">Mahdi Salahshour</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shafiee,+A">Amirahmad Shafiee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tefagh,+M">Mojtaba Tefagh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computational Finance (q-fin.CP) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/2411.17350" title="Abstract" id="2411.17350"> arXiv:2411.17350 </a> [<a href="/pdf/2411.17350" title="Download PDF" id="pdf-2411.17350" aria-labelledby="pdf-2411.17350">pdf</a>, <a href="https://arxiv.org/html/2411.17350v1" title="View HTML" id="html-2411.17350" aria-labelledby="html-2411.17350" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17350" title="Other formats" id="oth-2411.17350" aria-labelledby="oth-2411.17350">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bei,+Y">Yuanchen Bei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+W">Weizhi Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+H">Hao Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+S">Sheng Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+C">Carl Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fan,+J">Jiapei Fan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+L">Longtao Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bu,+J">Jiajun Bu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 14 pages, accepted by KDD2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Social and Information Networks (cs.SI) </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2411.17337" title="Abstract" id="2411.17337"> arXiv:2411.17337 </a> [<a href="/pdf/2411.17337" title="Download PDF" id="pdf-2411.17337" aria-labelledby="pdf-2411.17337">pdf</a>, <a href="https://arxiv.org/html/2411.17337v1" title="View HTML" id="html-2411.17337" aria-labelledby="html-2411.17337" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17337" title="Other formats" id="oth-2411.17337" aria-labelledby="oth-2411.17337">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> sbi reloaded: a toolkit for simulation-based inference workflows </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Boelts,+J">Jan Boelts</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deistler,+M">Michael Deistler</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gloeckler,+M">Manuel Gloeckler</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tejero-Cantero,+%C3%81">脕lvaro Tejero-Cantero</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lueckmann,+J">Jan-Matthis Lueckmann</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moss,+G">Guy Moss</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Steinbach,+P">Peter Steinbach</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moreau,+T">Thomas Moreau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Muratore,+F">Fabio Muratore</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Linhart,+J">Julia Linhart</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Durkan,+C">Conor Durkan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vetter,+J">Julius Vetter</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Miller,+B+K">Benjamin Kurt Miller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Herold,+M">Maternus Herold</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ziaeemehr,+A">Abolfazl Ziaeemehr</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pals,+M">Matthijs Pals</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gruner,+T">Theo Gruner</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bischoff,+S">Sebastian Bischoff</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Krouglova,+N">Nastya Krouglova</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+R">Richard Gao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lappalainen,+J+K">Janne K. Lappalainen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mucs%C3%A1nyi,+B">B谩lint Mucs谩nyi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pei,+F">Felix Pei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schulz,+A">Auguste Schulz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stefanidi,+Z">Zinovia Stefanidi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rodrigues,+P">Pedro Rodrigues</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schr%C3%B6der,+C">Cornelius Schr枚der</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zaid,+F+A">Faried Abu Zaid</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Beck,+J">Jonas Beck</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kapoor,+J">Jaivardhan Kapoor</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Greenberg,+D+S">David S. Greenberg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gon%C3%A7alves,+P+J">Pedro J. Gon莽alves</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Macke,+J+H">Jakob H. Macke</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='item34'>[34]</a> <a href ="/abs/2411.17332" title="Abstract" id="2411.17332"> arXiv:2411.17332 </a> [<a href="/pdf/2411.17332" title="Download PDF" id="pdf-2411.17332" aria-labelledby="pdf-2411.17332">pdf</a>, <a href="https://arxiv.org/html/2411.17332v1" title="View HTML" id="html-2411.17332" aria-labelledby="html-2411.17332" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17332" title="Other formats" id="oth-2411.17332" aria-labelledby="oth-2411.17332">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Generalization of Handwritten Text Recognition Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Garrido-Munoz,+C">Carlos Garrido-Munoz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Calvo-Zaragoza,+J">Jorge Calvo-Zaragoza</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='item35'>[35]</a> <a href ="/abs/2411.17296" title="Abstract" id="2411.17296"> arXiv:2411.17296 </a> [<a href="/pdf/2411.17296" title="Download PDF" id="pdf-2411.17296" aria-labelledby="pdf-2411.17296">pdf</a>, <a href="https://arxiv.org/html/2411.17296v1" title="View HTML" id="html-2411.17296" aria-labelledby="html-2411.17296" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17296" title="Other formats" id="oth-2411.17296" aria-labelledby="oth-2411.17296">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ai,+G">Guoguo Ai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pang,+G">Guansong Pang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Qiao,+H">Hezhe Qiao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+Y">Yuan Gao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yan,+H">Hui Yan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 13 pages, 6 figures, 7tables </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='item36'>[36]</a> <a href ="/abs/2411.17291" title="Abstract" id="2411.17291"> arXiv:2411.17291 </a> [<a href="/pdf/2411.17291" title="Download PDF" id="pdf-2411.17291" aria-labelledby="pdf-2411.17291">pdf</a>, <a href="/format/2411.17291" title="Other formats" id="oth-2411.17291" aria-labelledby="oth-2411.17291">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Interpretable label-free self-guided subspace clustering </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kopriva,+I">Ivica Kopriva</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 45 pages; 3 figures; 10 tables </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='item37'>[37]</a> <a href ="/abs/2411.17287" title="Abstract" id="2411.17287"> arXiv:2411.17287 </a> [<a href="/pdf/2411.17287" title="Download PDF" id="pdf-2411.17287" aria-labelledby="pdf-2411.17287">pdf</a>, <a href="https://arxiv.org/html/2411.17287v1" title="View HTML" id="html-2411.17287" aria-labelledby="html-2411.17287" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17287" title="Other formats" id="oth-2411.17287" aria-labelledby="oth-2411.17287">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Privacy Preserving Federated Unsupervised Domain Adaptation with Application to Age Prediction from DNA Methylation Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Baykara,+C+A">Cem Ata Baykara</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=%C3%9Cnal,+A+B">Ali Burak 脺nal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pfeifer,+N">Nico Pfeifer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Akg%C3%BCn,+M">Mete Akg眉n</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='item38'>[38]</a> <a href ="/abs/2411.17284" title="Abstract" id="2411.17284"> arXiv:2411.17284 </a> [<a href="/pdf/2411.17284" title="Download PDF" id="pdf-2411.17284" aria-labelledby="pdf-2411.17284">pdf</a>, <a href="https://arxiv.org/html/2411.17284v1" title="View HTML" id="html-2411.17284" aria-labelledby="html-2411.17284" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17284" title="Other formats" id="oth-2411.17284" aria-labelledby="oth-2411.17284">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Using Large Language Models for Expert Prior Elicitation in Predictive Modelling </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Capstick,+A">Alexander Capstick</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Krishnan,+R+G">Rahul G. Krishnan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Barnaghi,+P">Payam Barnaghi</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='item39'>[39]</a> <a href ="/abs/2411.17278" title="Abstract" id="2411.17278"> arXiv:2411.17278 </a> [<a href="/pdf/2411.17278" title="Download PDF" id="pdf-2411.17278" aria-labelledby="pdf-2411.17278">pdf</a>, <a href="https://arxiv.org/html/2411.17278v1" title="View HTML" id="html-2411.17278" aria-labelledby="html-2411.17278" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17278" title="Other formats" id="oth-2411.17278" aria-labelledby="oth-2411.17278">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Exploration of Neural Collapse under Imbalanced Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+H">Haixia Liu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26pages, 4figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/2411.17257" title="Abstract" id="2411.17257"> arXiv:2411.17257 </a> [<a href="/pdf/2411.17257" title="Download PDF" id="pdf-2411.17257" aria-labelledby="pdf-2411.17257">pdf</a>, <a href="https://arxiv.org/html/2411.17257v1" title="View HTML" id="html-2411.17257" aria-labelledby="html-2411.17257" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17257" title="Other formats" id="oth-2411.17257" aria-labelledby="oth-2411.17257">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+Y">Yuang Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+T">Tianyu Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J">Jiadong Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ye,+S">Shenrong Ye</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+F">Fuxin Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+T">Tieying Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+X">Xiaofeng Gao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This work is submitted to IEEE International Conference on Data Engineering (ICDE) 2025 </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='item41'>[41]</a> <a href ="/abs/2411.17255" title="Abstract" id="2411.17255"> arXiv:2411.17255 </a> [<a href="/pdf/2411.17255" title="Download PDF" id="pdf-2411.17255" aria-labelledby="pdf-2411.17255">pdf</a>, <a href="/format/2411.17255" title="Other formats" id="oth-2411.17255" aria-labelledby="oth-2411.17255">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> APT: Architectural Planning and Text-to-Blueprint Construction Using Large Language Models for Open-World Agents </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+J+Y">Jun Yu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+T">Tao Gao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2411.17236" title="Abstract" id="2411.17236"> arXiv:2411.17236 </a> [<a href="/pdf/2411.17236" title="Download PDF" id="pdf-2411.17236" aria-labelledby="pdf-2411.17236">pdf</a>, <a href="https://arxiv.org/html/2411.17236v1" title="View HTML" id="html-2411.17236" aria-labelledby="html-2411.17236" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17236" title="Other formats" id="oth-2411.17236" aria-labelledby="oth-2411.17236">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Graph Diffusion to Graph Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xian,+J+J+C">Jia Jun Cheng Xian</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mahdavi,+S">Sadegh Mahdavi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liao,+R">Renjie Liao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schulte,+O">Oliver Schulte</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='item43'>[43]</a> <a href ="/abs/2411.17218" title="Abstract" id="2411.17218"> arXiv:2411.17218 </a> [<a href="/pdf/2411.17218" title="Download PDF" id="pdf-2411.17218" aria-labelledby="pdf-2411.17218">pdf</a>, <a href="https://arxiv.org/html/2411.17218v1" title="View HTML" id="html-2411.17218" aria-labelledby="html-2411.17218" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17218" title="Other formats" id="oth-2411.17218" aria-labelledby="oth-2411.17218">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+W">Weiqi Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Z">Zhiqiang Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wen,+Q">Qingsong Wen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+L">Liang Sun</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='item44'>[44]</a> <a href ="/abs/2411.17207" title="Abstract" id="2411.17207"> arXiv:2411.17207 </a> [<a href="/pdf/2411.17207" title="Download PDF" id="pdf-2411.17207" aria-labelledby="pdf-2411.17207">pdf</a>, <a href="https://arxiv.org/html/2411.17207v1" title="View HTML" id="html-2411.17207" aria-labelledby="html-2411.17207" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17207" title="Other formats" id="oth-2411.17207" aria-labelledby="oth-2411.17207">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Efficiency of NLP-Inspired Methods for Tabular Deep Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Thielmann,+A+F">Anton Frederik Thielmann</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Samiee,+S">Soheila Samiee</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/2411.17201" title="Abstract" id="2411.17201"> arXiv:2411.17201 </a> [<a href="/pdf/2411.17201" title="Download PDF" id="pdf-2411.17201" aria-labelledby="pdf-2411.17201">pdf</a>, <a href="/format/2411.17201" title="Other formats" id="oth-2411.17201" aria-labelledby="oth-2411.17201">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Fu,+H">Hengyu Fu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Z">Zihao Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nichani,+E">Eshaan Nichani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+J+D">Jason D. Lee</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 78 pages, 4 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Statistics Theory (math.ST); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/2411.17182" title="Abstract" id="2411.17182"> arXiv:2411.17182 </a> [<a href="/pdf/2411.17182" title="Download PDF" id="pdf-2411.17182" aria-labelledby="pdf-2411.17182">pdf</a>, <a href="https://arxiv.org/html/2411.17182v1" title="View HTML" id="html-2411.17182" aria-labelledby="html-2411.17182" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17182" title="Other formats" id="oth-2411.17182" aria-labelledby="oth-2411.17182">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+Y">Yunzhe Hu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zou,+D">Difan Zou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+D">Dong Xu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NeurIPS 2024 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/2411.17164" title="Abstract" id="2411.17164"> arXiv:2411.17164 </a> [<a href="/pdf/2411.17164" title="Download PDF" id="pdf-2411.17164" aria-labelledby="pdf-2411.17164">pdf</a>, <a href="https://arxiv.org/html/2411.17164v1" title="View HTML" id="html-2411.17164" aria-labelledby="html-2411.17164" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17164" title="Other formats" id="oth-2411.17164" aria-labelledby="oth-2411.17164">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Nabian,+M+A">Mohammad Amin Nabian</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computational Physics (physics.comp-ph) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/2411.17132" title="Abstract" id="2411.17132"> arXiv:2411.17132 </a> [<a href="/pdf/2411.17132" title="Download PDF" id="pdf-2411.17132" aria-labelledby="pdf-2411.17132">pdf</a>, <a href="https://arxiv.org/html/2411.17132v1" title="View HTML" id="html-2411.17132" aria-labelledby="html-2411.17132" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17132" title="Other formats" id="oth-2411.17132" aria-labelledby="oth-2411.17132">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improving Resistance to Noisy Label Fitting by Reweighting Gradient in SAM </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Luong,+H">Hoang-Chau Luong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nguyen-Quang,+T">Thuc Nguyen-Quang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tran,+M">Minh-Triet Tran</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='item49'>[49]</a> <a href ="/abs/2411.17128" title="Abstract" id="2411.17128"> arXiv:2411.17128 </a> [<a href="/pdf/2411.17128" title="Download PDF" id="pdf-2411.17128" aria-labelledby="pdf-2411.17128">pdf</a>, <a href="https://arxiv.org/html/2411.17128v1" title="View HTML" id="html-2411.17128" aria-labelledby="html-2411.17128" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17128" title="Other formats" id="oth-2411.17128" aria-labelledby="oth-2411.17128">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Enhancing Imbalance Learning: A Novel Slack-Factor Fuzzy SVM Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tanveer,+M">M. Tanveer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tiwari,+A">Anushka Tiwari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Akhtar,+M">Mushir Akhtar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lin,+C">C.T. Lin</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='item50'>[50]</a> <a href ="/abs/2411.17126" title="Abstract" id="2411.17126"> arXiv:2411.17126 </a> [<a href="/pdf/2411.17126" title="Download PDF" id="pdf-2411.17126" aria-labelledby="pdf-2411.17126">pdf</a>, <a href="https://arxiv.org/html/2411.17126v1" title="View HTML" id="html-2411.17126" aria-labelledby="html-2411.17126" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2411.17126" title="Other formats" id="oth-2411.17126" aria-labelledby="oth-2411.17126">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> From Machine Learning to Machine Unlearning: Complying with GDPR's Right to be Forgotten while Maintaining Business Value of Predictive Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yuncong Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Han,+X">Xiao Han</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chai,+Y">Yidong Chai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ebrahimi,+R">Reza Ebrahimi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Behnia,+R">Rouzbeh Behnia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Padmanabhan,+B">Balaji Padmanabhan</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 733 entries : <span>1-50</span> <a href=/list/cs.LG/recent?skip=50&show=50>51-100</a> <a href=/list/cs.LG/recent?skip=100&show=50>101-150</a> <a href=/list/cs.LG/recent?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/recent?skip=700&show=50>701-733</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/recent?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/recent?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/recent?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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