Computer Science Feb 2022

<!DOCTYPE html> <html lang="en"> <head> <title>Computer Science Feb 2022</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <link rel="apple-touch-icon" sizes="180x180" href="/static/browse/0.3.4/images/icons/apple-touch-icon.png"> <link rel="icon" type="image/png" sizes="32x32" href="/static/browse/0.3.4/images/icons/favicon-32x32.png"> <link rel="icon" type="image/png" sizes="16x16" href="/static/browse/0.3.4/images/icons/favicon-16x16.png"> <link rel="manifest" href="/static/browse/0.3.4/images/icons/site.webmanifest"> <link rel="mask-icon" href="/static/browse/0.3.4/images/icons/safari-pinned-tab.svg" color="#5bbad5"> <meta name="msapplication-TileColor" content="#da532c"> <meta name="theme-color" content="#ffffff"> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/arXiv.css?v=20241206" /> <link rel="stylesheet" type="text/css" media="print" href="/static/browse/0.3.4/css/arXiv-print.css?v=20200611" /> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/browse_search.css" /> <script language="javascript" src="/static/browse/0.3.4/js/accordion.js" /></script> <script src="/static/browse/0.3.4/js/mathjaxToggle.min.js" type="text/javascript"></script> <script type="text/javascript" language="javascript">mathjaxToggle();</script> </head> <body class="with-cu-identity"> <div class="flex-wrap-footer"> <header> <a href="#content" class="is-sr-only">Skip to main content</a>  <div class="columns is-vcentered is-hidden-mobile" id="cu-identity"> <div class="column" id="cu-logo"> <a href="https://www.cornell.edu/"><img src="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg" alt="Cornell University" /></a> </div><div class="column" id="support-ack"> <span id="support-ack-url">We gratefully acknowledge support from the Simons Foundation, <a href="https://info.arxiv.org/about/ourmembers.html">member institutions</a>, and all contributors.</span> <a href="https://info.arxiv.org/about/donate.html" class="btn-header-donate">Donate</a> </div> </div> <div id="header" class="is-hidden-mobile"> <a aria-hidden="true" tabindex="-1" href="/IgnoreMe"></a> <div class="header-breadcrumbs"> <a href="/"><img src="/static/browse/0.3.4/images/arxiv-logo-one-color-white.svg" alt="arxiv logo" style="height:40px;"/></a> <span>></span> <a href="/list/cs/recent">cs</a> </div> <div class="search-block level-right"> <form class="level-item mini-search" method="GET" action="https://arxiv.org/search"> <div class="field has-addons"> <div class="control"> <input class="input is-small" type="text" name="query" placeholder="Search..." aria-label="Search term or terms" /> <p class="help"><a href="https://info.arxiv.org/help">Help</a> | <a href="https://arxiv.org/search/advanced">Advanced Search</a></p> </div> <div class="control"> <div class="select is-small"> <select name="searchtype" aria-label="Field to search"> <option value="all" selected="selected">All fields</option> <option value="title">Title</option> <option value="author">Author</option> <option value="abstract">Abstract</option> <option value="comments">Comments</option> <option value="journal_ref">Journal reference</option> <option value="acm_class">ACM classification</option> <option value="msc_class">MSC classification</option> <option value="report_num">Report number</option> <option value="paper_id">arXiv identifier</option> <option value="doi">DOI</option> <option value="orcid">ORCID</option> <option value="author_id">arXiv author ID</option> <option value="help">Help pages</option> <option value="full_text">Full text</option> </select> </div> </div> <input type="hidden" name="source" value="header"> <button class="button is-small is-cul-darker">Search</button> </div> </form> </div> </div> <div class="mobile-header"> <div class="columns is-mobile"> <div class="column logo-arxiv"><a href="https://arxiv.org/"><img src="/static/browse/0.3.4/images/arxiv-logomark-small-white.svg" alt="arXiv logo" style="height:60px;" /></a></div> <div class="column logo-cornell"><a href="https://www.cornell.edu/"> <picture> <source media="(min-width: 501px)" srcset="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg 400w" sizes="400w" /> <source srcset="/static/browse/0.3.4/images/icons/cu/cornell_seal_simple_black.svg 2x" /> <img src="/static/browse/0.3.4/images/icons/cu/cornell-reduced-white-SMALL.svg" alt="Cornell University Logo" /> </picture> </a></div> <div class="column nav" id="toggle-container" role="menubar"> <button class="toggle-control"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-white"><title>open search</title><path d="M505 442.7L405.3 343c-4.5-4.5-10.6-7-17-7H372c27.6-35.3 44-79.7 44-128C416 93.1 322.9 0 208 0S0 93.1 0 208s93.1 208 208 208c48.3 0 92.7-16.4 128-44v16.3c0 6.4 2.5 12.5 7 17l99.7 99.7c9.4 9.4 24.6 9.4 33.9 0l28.3-28.3c9.4-9.4 9.4-24.6.1-34zM208 336c-70.7 0-128-57.2-128-128 0-70.7 57.2-128 128-128 70.7 0 128 57.2 128 128 0 70.7-57.2 128-128 128z"/></svg></button> <div class="mobile-toggle-block toggle-target"> <form class="mobile-search-form" method="GET" action="https://arxiv.org/search"> <div class="field has-addons"> <input class="input" type="text" name="query" placeholder="Search..." aria-label="Search term or terms" /> <input type="hidden" name="source" value="header"> <input type="hidden" name="searchtype" value="all"> <button class="button">GO</button> </div> </form> </div> <button class="toggle-control"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" class="icon filter-white" role="menu"><title>open navigation menu</title><path d="M16 132h416c8.837 0 16-7.163 16-16V76c0-8.837-7.163-16-16-16H16C7.163 60 0 67.163 0 76v40c0 8.837 7.163 16 16 16zm0 160h416c8.837 0 16-7.163 16-16v-40c0-8.837-7.163-16-16-16H16c-8.837 0-16 7.163-16 16v40c0 8.837 7.163 16 16 16zm0 160h416c8.837 0 16-7.163 16-16v-40c0-8.837-7.163-16-16-16H16c-8.837 0-16 7.163-16 16v40c0 8.837 7.163 16 16 16z"/ ></svg></button> <div class="mobile-toggle-block toggle-target"> <nav class="mobile-menu" aria-labelledby="mobilemenulabel"> <h2 id="mobilemenulabel">quick links</h2> <ul> <li><a href="https://arxiv.org/login">Login</a></li> <li><a href="https://info.arxiv.org/help">Help Pages</a></li> <li><a href="https://info.arxiv.org/about">About</a></li> </ul> </nav> </div> </div> </div> </div> </header> <main> <div id="content"> <div id='content-inner'> <div id='dlpage'> <h1>Computer Science</h1> <h2>Authors and titles for February 2022 </h2> <div class='paging'>Total of 6235 entries : <span>1-50</span> <a href=/list/cs/2022-02?skip=50&show=50>51-100</a> <a href=/list/cs/2022-02?skip=100&show=50>101-150</a> <a href=/list/cs/2022-02?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs/2022-02?skip=6200&show=50>6201-6235</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs/2022-02?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs/2022-02?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs/2022-02?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/2202.00003" title="Abstract" id="2202.00003"> arXiv:2202.00003 </a> [<a href="/pdf/2202.00003" title="Download PDF" id="pdf-2202.00003" aria-labelledby="pdf-2202.00003">pdf</a>, <a href="/format/2202.00003" title="Other formats" id="oth-2202.00003" aria-labelledby="oth-2202.00003">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Green NFTs: A Study on the Environmental Impact of Cryptoart Technologies </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Marro,+S">Samuele Marro</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Donno,+L">Luca Donno</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This draft was written in May 2021 and might be subject to modifications. August 29th 2022: removed references to old emission figure </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span> </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2202.00004" title="Abstract" id="2202.00004"> arXiv:2202.00004 </a> [<a href="/pdf/2202.00004" title="Download PDF" id="pdf-2202.00004" aria-labelledby="pdf-2202.00004">pdf</a>, <a href="/format/2202.00004" title="Other formats" id="oth-2202.00004" aria-labelledby="oth-2202.00004">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Polynomial Approximation of Activation Function </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chiang,+J">John Chiang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> In this work, we proposed an interesting method to approximate the activation function by a polynomial the degree of which is preset low. Our method to approximate the activation function is much more flexible compared to the least square method in the sense that the additional parameters could better control the shape of the resulting polynomial to approximate </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2202.00005" title="Abstract" id="2202.00005"> arXiv:2202.00005 </a> [<a href="/pdf/2202.00005" title="Download PDF" id="pdf-2202.00005" aria-labelledby="pdf-2202.00005">pdf</a>, <a href="/format/2202.00005" title="Other formats" id="oth-2202.00005" aria-labelledby="oth-2202.00005">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> 5G enabled Mobile Edge Computing security for Autonomous Vehicles </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=D'Costa,+D+R">Daryll Ralph D'Costa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Abbas,+R">Robert Abbas</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 9 pages, 8 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2202.00008" title="Abstract" id="2202.00008"> arXiv:2202.00008 </a> [<a href="/pdf/2202.00008" title="Download PDF" id="pdf-2202.00008" aria-labelledby="pdf-2202.00008">pdf</a>, <a href="/format/2202.00008" title="Other formats" id="oth-2202.00008" aria-labelledby="oth-2202.00008">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MEGA: Model Stealing via Collaborative Generator-Substitute Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hong,+C">Chi Hong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+J">Jiyue Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+L+Y">Lydia Y. Chen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2202.00009" title="Abstract" id="2202.00009"> arXiv:2202.00009 </a> [<a href="/pdf/2202.00009" title="Download PDF" id="pdf-2202.00009" aria-labelledby="pdf-2202.00009">pdf</a>, <a href="/format/2202.00009" title="Other formats" id="oth-2202.00009" aria-labelledby="oth-2202.00009">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Identifying Dementia Subtypes with Electronic Health Records </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kumar,+S">Sayantan Kumar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Abrams,+Z">Zachary Abrams</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schindler,+S">Suzanne Schindler</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ghoshal,+N">Nupur Ghoshal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Payne,+P">Philip Payne</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ACM Conference on Bioinformatics, Computational Biology, and Health Informatics 13 pages, 7 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='item6'>[6]</a> <a href ="/abs/2202.00035" title="Abstract" id="2202.00035"> arXiv:2202.00035 </a> [<a href="/pdf/2202.00035" title="Download PDF" id="pdf-2202.00035" aria-labelledby="pdf-2202.00035">pdf</a>, <a href="/format/2202.00035" title="Other formats" id="oth-2202.00035" aria-labelledby="oth-2202.00035">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Fair Representations via Rate-Distortion Maximization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chowdhury,+S+B+R">Somnath Basu Roy Chowdhury</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chaturvedi,+S">Snigdha Chaturvedi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at TACL </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2202.00045" title="Abstract" id="2202.00045"> arXiv:2202.00045 </a> [<a href="/pdf/2202.00045" title="Download PDF" id="pdf-2202.00045" aria-labelledby="pdf-2202.00045">pdf</a>, <a href="/format/2202.00045" title="Other formats" id="oth-2202.00045" aria-labelledby="oth-2202.00045">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Alkhatib,+N">Natasha Alkhatib</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mushtaq,+M">Maria Mushtaq</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ghauch,+H">Hadi Ghauch</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Danger,+J">Jean-Luc Danger</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); Networking and Internet Architecture (cs.NI) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2202.00046" title="Abstract" id="2202.00046"> arXiv:2202.00046 </a> [<a href="/pdf/2202.00046" title="Download PDF" id="pdf-2202.00046" aria-labelledby="pdf-2202.00046">pdf</a>, <a href="/format/2202.00046" title="Other formats" id="oth-2202.00046" aria-labelledby="oth-2202.00046">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Finding Directions in GAN's Latent Space for Neural Face Reenactment </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bounareli,+S">Stella Bounareli</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Argyriou,+V">Vasileios Argyriou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tzimiropoulos,+G">Georgios Tzimiropoulos</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for publication in BMVC 2022. Project page: <a href="https://stelabou.github.io/stylegan-directions-reenactment/" rel="external noopener nofollow" class="link-external link-https">this https URL</a> Code: <a href="https://github.com/StelaBou/stylegan_directions_face_reenactment" 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">Computer Vision and Pattern Recognition (cs.CV)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2202.00047" title="Abstract" id="2202.00047"> arXiv:2202.00047 </a> [<a href="/pdf/2202.00047" title="Download PDF" id="pdf-2202.00047" aria-labelledby="pdf-2202.00047">pdf</a>, <a href="/format/2202.00047" title="Other formats" id="oth-2202.00047" aria-labelledby="oth-2202.00047">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Stories We Tell About Data: Media Types for Data-Driven Storytelling </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+Z">Zhenpeng Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Elmqvist,+N">Niklas Elmqvist</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Human-Computer Interaction (cs.HC)</span> </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2202.00050" title="Abstract" id="2202.00050"> arXiv:2202.00050 </a> [<a href="/pdf/2202.00050" title="Download PDF" id="pdf-2202.00050" aria-labelledby="pdf-2202.00050">pdf</a>, <a href="/format/2202.00050" title="Other formats" id="oth-2202.00050" aria-labelledby="oth-2202.00050">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shekarizadeh,+S">Soroor Shekarizadeh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rastgoo,+R">Razieh Rastgoo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Al-Kuwari,+S">Saif Al-Kuwari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sabokrou,+M">Mohammad Sabokrou</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Vision and Pattern Recognition (cs.CV)</span> </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2202.00056" title="Abstract" id="2202.00056"> arXiv:2202.00056 </a> [<a href="/pdf/2202.00056" title="Download PDF" id="pdf-2202.00056" aria-labelledby="pdf-2202.00056">pdf</a>, <a href="/format/2202.00056" title="Other formats" id="oth-2202.00056" aria-labelledby="oth-2202.00056">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Accurate Link Lifetime Computation in Autonomous Airborne UAV Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Garg,+S">Shivam Garg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ihler,+A">Alexander Ihler</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kumar,+S">Sunil Kumar</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Mathematical framework to accurately compute link lifetime in an airborne network </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Networking and Internet Architecture (cs.NI)</span>; Robotics (cs.RO) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2202.00057" title="Abstract" id="2202.00057"> arXiv:2202.00057 </a> [<a href="/pdf/2202.00057" title="Download PDF" id="pdf-2202.00057" aria-labelledby="pdf-2202.00057">pdf</a>, <a href="/format/2202.00057" title="Other formats" id="oth-2202.00057" aria-labelledby="oth-2202.00057">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Practical Efficient Microservice Autoscaling with QoS Assurance </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hossen,+M+R">Md Rajib Hossen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Islam,+M+A">Mohammad A. Islam</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ahmed,+K">Kishwar Ahmed</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Appeared on HPDC'22, 13 pages, 20 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Distributed, Parallel, and Cluster Computing (cs.DC)</span>; Systems and Control (eess.SY) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2202.00060" title="Abstract" id="2202.00060"> arXiv:2202.00060 </a> [<a href="/pdf/2202.00060" title="Download PDF" id="pdf-2202.00060" aria-labelledby="pdf-2202.00060">pdf</a>, <a href="/format/2202.00060" title="Other formats" id="oth-2202.00060" aria-labelledby="oth-2202.00060">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SnAKe: Bayesian Optimization with Pathwise Exploration </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Folch,+J+P">Jose Pablo Folch</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+S">Shiqiang Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lee,+R+M">Robert M Lee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shafei,+B">Behrang Shafei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Walz,+D">David Walz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tsay,+C">Calvin Tsay</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=van+der+Wilk,+M">Mark van der Wilk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Misener,+R">Ruth Misener</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 main pages, 39 with appendix, 30 figures, 10 tables. Final camera-ready version for NeurIPS, with supplementary material included </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='item14'>[14]</a> <a href ="/abs/2202.00062" title="Abstract" id="2202.00062"> arXiv:2202.00062 </a> [<a href="/pdf/2202.00062" title="Download PDF" id="pdf-2202.00062" aria-labelledby="pdf-2202.00062">pdf</a>, <a href="/format/2202.00062" title="Other formats" id="oth-2202.00062" aria-labelledby="oth-2202.00062">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Monte Carlo stochastic Galerkin methods for non-Maxwellian kinetic models of multiagent systems with uncertainties </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Medaglia,+A">Andrea Medaglia</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Tosin,+A">Andrea Tosin</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Zanella,+M">Mattia Zanella</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 28 pages, 8 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Partial Differ. Equ. Appl., 3(4):51, 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Numerical Analysis (math.NA)</span>; Adaptation and Self-Organizing Systems (nlin.AO); Physics and Society (physics.soc-ph) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2202.00063" title="Abstract" id="2202.00063"> arXiv:2202.00063 </a> [<a href="/pdf/2202.00063" title="Download PDF" id="pdf-2202.00063" aria-labelledby="pdf-2202.00063">pdf</a>, <a href="/format/2202.00063" title="Other formats" id="oth-2202.00063" aria-labelledby="oth-2202.00063">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+X">Xuezhou Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+Y">Yuda Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Uehara,+M">Masatoshi Uehara</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+M">Mengdi Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Agarwal,+A">Alekh Agarwal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+W">Wen 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='item16'>[16]</a> <a href ="/abs/2202.00065" title="Abstract" id="2202.00065"> arXiv:2202.00065 </a> [<a href="/pdf/2202.00065" title="Download PDF" id="pdf-2202.00065" aria-labelledby="pdf-2202.00065">pdf</a>, <a href="/format/2202.00065" title="Other formats" id="oth-2202.00065" aria-labelledby="oth-2202.00065">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning affective meanings that derives the social behavior using Bidirectional Encoder Representations from Transformers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mostafavi,+M">Moeen Mostafavi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Porter,+M+D">Michael D. Porter</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Robinson,+D+T">Dawn T. Robinson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Working paper </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation and Language (cs.CL)</span> </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2202.00069" title="Abstract" id="2202.00069"> arXiv:2202.00069 </a> [<a href="/pdf/2202.00069" title="Download PDF" id="pdf-2202.00069" aria-labelledby="pdf-2202.00069">pdf</a>, <a href="/format/2202.00069" title="Other formats" id="oth-2202.00069" aria-labelledby="oth-2202.00069">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> "How trustworthy is this research?" Designing a Tool to Help Readers Understand Evidence and Uncertainty in Science Journalism </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=L%C3%B8vlie,+A+S">Anders Sundnes L酶vlie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Waagstein,+A">Astrid Waagstein</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hyldg%C3%A5rd,+P">Peter Hyldg氓rd</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Anders Sundnes L{\o}vlie, Astrid Waagstein & Peter Hyldg{\aa}rd (2023) 'How Trustworthy Is This Research?' Designing a Tool to Help Readers Understand Evidence and Uncertainty in Science Journalism, Digital Journalism </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Digital Libraries (cs.DL)</span>; Human-Computer Interaction (cs.HC) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2202.00070" title="Abstract" id="2202.00070"> arXiv:2202.00070 </a> [<a href="/pdf/2202.00070" title="Download PDF" id="pdf-2202.00070" aria-labelledby="pdf-2202.00070">pdf</a>, <a href="/format/2202.00070" title="Other formats" id="oth-2202.00070" aria-labelledby="oth-2202.00070">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Implicit Concept Drift Detection for Multi-label Data Streams </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Gulcan,+E+B">Ege Berkay Gulcan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Can,+F">Fazli Can</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 18 pages, 7 figures, submitted to Artificial Intelligence Review </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Retrieval (cs.IR) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2202.00071" title="Abstract" id="2202.00071"> arXiv:2202.00071 </a> [<a href="/pdf/2202.00071" title="Download PDF" id="pdf-2202.00071" aria-labelledby="pdf-2202.00071">pdf</a>, <a href="/format/2202.00071" title="Other formats" id="oth-2202.00071" aria-labelledby="oth-2202.00071">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Qian,+C">Cheng Qian</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+K">Kejun Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Glass,+L">Lucas Glass</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=S.,+R">Rakshith S. Srinivasa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+J">Jimeng Sun</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Retrieval (cs.IR); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/2202.00074" title="Abstract" id="2202.00074"> arXiv:2202.00074 </a> [<a href="/pdf/2202.00074" title="Download PDF" id="pdf-2202.00074" aria-labelledby="pdf-2202.00074">pdf</a>, <a href="/format/2202.00074" title="Other formats" id="oth-2202.00074" aria-labelledby="oth-2202.00074">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Cui,+T">Tiangang Cui</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Tong,+X">Xin Tong</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Zahm,+O">Olivier Zahm</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Inverse Problems 38 (2022) pp. 124002 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Numerical Analysis (math.NA)</span> </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/2202.00075" title="Abstract" id="2202.00075"> arXiv:2202.00075 </a> [<a href="/pdf/2202.00075" title="Download PDF" id="pdf-2202.00075" aria-labelledby="pdf-2202.00075">pdf</a>, <a href="/format/2202.00075" title="Other formats" id="oth-2202.00075" aria-labelledby="oth-2202.00075">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xue,+Z">Zihui Xue</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yuedong Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+M">Mengtian Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Marculescu,+R">Radu Marculescu</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='item22'>[22]</a> <a href ="/abs/2202.00079" title="Abstract" id="2202.00079"> arXiv:2202.00079 </a> [<a href="/pdf/2202.00079" title="Download PDF" id="pdf-2202.00079" aria-labelledby="pdf-2202.00079">pdf</a>, <a href="/format/2202.00079" title="Other formats" id="oth-2202.00079" aria-labelledby="oth-2202.00079">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> You May Not Need Ratio Clipping in PPO </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+M">Mingfei Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kurin,+V">Vitaly Kurin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+G">Guoqing Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Devlin,+S">Sam Devlin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Qin,+T">Tao Qin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hofmann,+K">Katja Hofmann</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Whiteson,+S">Shimon Whiteson</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2202.00082" title="Abstract" id="2202.00082"> arXiv:2202.00082 </a> [<a href="/pdf/2202.00082" title="Download PDF" id="pdf-2202.00082" aria-labelledby="pdf-2202.00082">pdf</a>, <a href="/format/2202.00082" title="Other formats" id="oth-2202.00082" aria-labelledby="oth-2202.00082">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Trust Region Bounds for Decentralized PPO Under Non-stationarity </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+M">Mingfei Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Devlin,+S">Sam Devlin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Beck,+J">Jacob Beck</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hofmann,+K">Katja Hofmann</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Whiteson,+S">Shimon Whiteson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> AAMAS 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2202.00088" title="Abstract" id="2202.00088"> arXiv:2202.00088 </a> [<a href="/pdf/2202.00088" title="Download PDF" id="pdf-2202.00088" aria-labelledby="pdf-2202.00088">pdf</a>, <a href="/format/2202.00088" title="Other formats" id="oth-2202.00088" aria-labelledby="oth-2202.00088">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reinforcement Learning with Heterogeneous Data: Estimation and Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+E+Y">Elynn Y. Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Song,+R">Rui Song</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jordan,+M+I">Michael I. Jordan</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2202.00089" title="Abstract" id="2202.00089"> arXiv:2202.00089 </a> [<a href="/pdf/2202.00089" title="Download PDF" id="pdf-2202.00089" aria-labelledby="pdf-2202.00089">pdf</a>, <a href="/format/2202.00089" title="Other formats" id="oth-2202.00089" aria-labelledby="oth-2202.00089">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Understanding AdamW through Proximal Methods and Scale-Freeness </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhuang,+Z">Zhenxun Zhuang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+M">Mingrui Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cutkosky,+A">Ashok Cutkosky</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Orabona,+F">Francesco Orabona</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/2202.00091" title="Abstract" id="2202.00091"> arXiv:2202.00091 </a> [<a href="/pdf/2202.00091" title="Download PDF" id="pdf-2202.00091" aria-labelledby="pdf-2202.00091">pdf</a>, <a href="/format/2202.00091" title="Other formats" id="oth-2202.00091" aria-labelledby="oth-2202.00091">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Vo,+V+Q">Viet Quoc Vo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Abbasnejad,+E">Ehsan Abbasnejad</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ranasinghe,+D+C">Damith C. Ranasinghe</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published as a conference paper at the International Conference on Learning Representations (ICLR 2022). Code is available at <a href="https://sparseevoattack.github.io/" 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); Cryptography and Security (cs.CR); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/2202.00094" title="Abstract" id="2202.00094"> arXiv:2202.00094 </a> [<a href="/pdf/2202.00094" title="Download PDF" id="pdf-2202.00094" aria-labelledby="pdf-2202.00094">pdf</a>, <a href="https://arxiv.org/html/2202.00094v2" title="View HTML" id="html-2202.00094" aria-labelledby="html-2202.00094" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2202.00094" title="Other formats" id="oth-2202.00094" aria-labelledby="oth-2202.00094">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Account credibility inference based on news-sharing networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Truong,+B+T">Bao Tran Truong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Allen,+O+M">Oliver Melbourne Allen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Menczer,+F">Filippo Menczer</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Social and Information Networks (cs.SI)</span> </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/2202.00096" title="Abstract" id="2202.00096"> arXiv:2202.00096 </a> [<a href="/pdf/2202.00096" title="Download PDF" id="pdf-2202.00096" aria-labelledby="pdf-2202.00096">pdf</a>, <a href="/format/2202.00096" title="Other formats" id="oth-2202.00096" aria-labelledby="oth-2202.00096">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Semi-supervised Identification and Mapping of Surface Water Extent using Street-level Monitoring Videos </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+R">Ruo-Qian Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ding,+Y">Yangmin Ding</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Vision and Pattern Recognition (cs.CV)</span> </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2202.00097" title="Abstract" id="2202.00097"> arXiv:2202.00097 </a> [<a href="/pdf/2202.00097" title="Download PDF" id="pdf-2202.00097" aria-labelledby="pdf-2202.00097">pdf</a>, <a href="/format/2202.00097" title="Other formats" id="oth-2202.00097" aria-labelledby="oth-2202.00097">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Self-supervised Graphs for Audio Representation Learning with Limited Labeled Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shirian,+A">Amir Shirian</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Somandepalli,+K">Krishna Somandepalli</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guha,+T">Tanaya Guha</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Sound (cs.SD) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2202.00102" title="Abstract" id="2202.00102"> arXiv:2202.00102 </a> [<a href="/pdf/2202.00102" title="Download PDF" id="pdf-2202.00102" aria-labelledby="pdf-2202.00102">pdf</a>, <a href="/format/2202.00102" title="Other formats" id="oth-2202.00102" aria-labelledby="oth-2202.00102">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Real-Time Facial Expression Recognition using Facial Landmarks and Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Haghpanah,+M+A">Mohammad Amin Haghpanah</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saeedizade,+E">Ehsan Saeedizade</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Masouleh,+M+T">Mehdi Tale Masouleh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kalhor,+A">Ahmad Kalhor</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 7 pages, 8 figures, 6 tables </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 (cs.LG) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/2202.00104" title="Abstract" id="2202.00104"> arXiv:2202.00104 </a> [<a href="/pdf/2202.00104" title="Download PDF" id="pdf-2202.00104" aria-labelledby="pdf-2202.00104">pdf</a>, <a href="/format/2202.00104" title="Other formats" id="oth-2202.00104" aria-labelledby="oth-2202.00104">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generalization in Cooperative Multi-Agent Systems </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mahajan,+A">Anuj Mahajan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Samvelyan,+M">Mikayel Samvelyan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gupta,+T">Tarun Gupta</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ellis,+B">Benjamin Ellis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+M">Mingfei Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rockt%C3%A4schel,+T">Tim Rockt盲schel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Whiteson,+S">Shimon Whiteson</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/2202.00113" title="Abstract" id="2202.00113"> arXiv:2202.00113 </a> [<a href="/pdf/2202.00113" title="Download PDF" id="pdf-2202.00113" aria-labelledby="pdf-2202.00113">pdf</a>, <a href="/format/2202.00113" title="Other formats" id="oth-2202.00113" aria-labelledby="oth-2202.00113">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Imbedding Deep Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Corbett,+A">Andrew Corbett</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kangin,+D">Dmitry Kangin</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted as a spotlight paper at the 10th International Conference on Learning Representations (ICLR), 2022 </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='item33'>[33]</a> <a href ="/abs/2202.00117" title="Abstract" id="2202.00117"> arXiv:2202.00117 </a> [<a href="/pdf/2202.00117" title="Download PDF" id="pdf-2202.00117" aria-labelledby="pdf-2202.00117">pdf</a>, <a href="/format/2202.00117" title="Other formats" id="oth-2202.00117" aria-labelledby="oth-2202.00117">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Continuous Forecasting via Neural Eigen Decomposition </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Belogolovsky,+S">Stav Belogolovsky</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Greenberg,+I">Ido Greenberg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Eitan,+D">Danny Eitan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mannor,+S">Shie Mannor</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) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/2202.00120" title="Abstract" id="2202.00120"> arXiv:2202.00120 </a> [<a href="/pdf/2202.00120" title="Download PDF" id="pdf-2202.00120" aria-labelledby="pdf-2202.00120">pdf</a>, <a href="/format/2202.00120" title="Other formats" id="oth-2202.00120" aria-labelledby="oth-2202.00120">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Perevalov,+A">Aleksandr Perevalov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Diefenbach,+D">Dennis Diefenbach</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Usbeck,+R">Ricardo Usbeck</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Both,+A">Andreas Both</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation and Language (cs.CL)</span>; Information Retrieval (cs.IR) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2202.00123" title="Abstract" id="2202.00123"> arXiv:2202.00123 </a> [<a href="/pdf/2202.00123" title="Download PDF" id="pdf-2202.00123" aria-labelledby="pdf-2202.00123">pdf</a>, <a href="/format/2202.00123" title="Other formats" id="oth-2202.00123" aria-labelledby="oth-2202.00123">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> 3D Visualization and Spatial Data Mining for Analysis of LULC Images </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kodge,+B+G">B. G. Kodge</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 7 figures and 3 tables </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> International Journal of Electrical, Electronics and Computer Science Engineering, Vol. 4, Issue 6, Dec-2017, P-ISSN: 2454-1222, E-ISSN: 2348-2273, pp-63-67 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Vision and Pattern Recognition (cs.CV)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2202.00126" title="Abstract" id="2202.00126"> arXiv:2202.00126 </a> [<a href="/pdf/2202.00126" title="Download PDF" id="pdf-2202.00126" aria-labelledby="pdf-2202.00126">pdf</a>, <a href="/format/2202.00126" title="Other formats" id="oth-2202.00126" aria-labelledby="oth-2202.00126">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Handling Bias in Toxic Speech Detection: A Survey </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Garg,+T">Tanmay Garg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Masud,+S">Sarah Masud</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Suresh,+T">Tharun Suresh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chakraborty,+T">Tanmoy Chakraborty</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted in ACM Computing Surveys, 30 pages, 5 figures, 7 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Social and Information Networks (cs.SI)</span>; Computers and Society (cs.CY); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2202.00128" title="Abstract" id="2202.00128"> arXiv:2202.00128 </a> [<a href="/pdf/2202.00128" title="Download PDF" id="pdf-2202.00128" aria-labelledby="pdf-2202.00128">pdf</a>, <a href="/format/2202.00128" title="Other formats" id="oth-2202.00128" aria-labelledby="oth-2202.00128">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reply to comment on "Failure of the simultaneous block diagonalization technique applied to complete and cluster synchronization of random networks" </div> <div class='list-authors'><a href="https://arxiv.org/search/eess?searchtype=author&query=Panahi,+S">Shirin Panahi</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Amaya,+N">Nelson Amaya</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Klickstein,+I">Isaac Klickstein</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Novello,+G">Galen Novello</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Sorrentino,+F">Francesco Sorrentino</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Systems and Control (eess.SY)</span> </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2202.00129" title="Abstract" id="2202.00129"> arXiv:2202.00129 </a> [<a href="/pdf/2202.00129" title="Download PDF" id="pdf-2202.00129" aria-labelledby="pdf-2202.00129">pdf</a>, <a href="/format/2202.00129" title="Other formats" id="oth-2202.00129" aria-labelledby="oth-2202.00129">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fundamental Limits for Sensor-Based Robot Control </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Majumdar,+A">Anirudha Majumdar</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mei,+Z">Zhiting Mei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pacelli,+V">Vincent Pacelli</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Extended version of paper presented at the 2022 Robotics: Science and Systems (RSS) conference </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Robotics (cs.RO)</span>; Artificial Intelligence (cs.AI); Information Theory (cs.IT); Machine Learning (cs.LG); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2202.00132" title="Abstract" id="2202.00132"> arXiv:2202.00132 </a> [<a href="/pdf/2202.00132" title="Download PDF" id="pdf-2202.00132" aria-labelledby="pdf-2202.00132">pdf</a>, <a href="/format/2202.00132" title="Other formats" id="oth-2202.00132" aria-labelledby="oth-2202.00132">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Submodularity In Machine Learning and Artificial Intelligence </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bilmes,+J">Jeff Bilmes</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='item40'>[40]</a> <a href ="/abs/2202.00134" title="Abstract" id="2202.00134"> arXiv:2202.00134 </a> [<a href="/pdf/2202.00134" title="Download PDF" id="pdf-2202.00134" aria-labelledby="pdf-2202.00134">pdf</a>, <a href="/format/2202.00134" title="Other formats" id="oth-2202.00134" aria-labelledby="oth-2202.00134">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Using Transition Learning to Enhance Mobile-Controlled Handoff In Decentralized Future Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Platt,+S">Steven Platt</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Demirel,+B">Berkay Demirel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Oliver,+M">Miquel Oliver</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 Pages, 13 figures, IEEE 5G World Forum 2021 </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 2021 IEEE 4th 5G World Forum (5GWF), 2021, pp. 424-429 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Networking and Internet Architecture (cs.NI)</span> </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/2202.00136" title="Abstract" id="2202.00136"> arXiv:2202.00136 </a> [<a href="/pdf/2202.00136" title="Download PDF" id="pdf-2202.00136" aria-labelledby="pdf-2202.00136">pdf</a>, <a href="/format/2202.00136" title="Other formats" id="oth-2202.00136" aria-labelledby="oth-2202.00136">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Non-adaptive and two-stage coding over the Z-channel </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lebedev,+A">Alexey Lebedev</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vorobyev,+I">Ilya Vorobyev</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lebedev,+V">Vladimir Lebedev</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deppe,+C">Christian Deppe</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Some references and known results, which were missed in the previous version, have been added </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Information Theory (cs.IT)</span>; Combinatorics (math.CO) </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2202.00137" title="Abstract" id="2202.00137"> arXiv:2202.00137 </a> [<a href="/pdf/2202.00137" title="Download PDF" id="pdf-2202.00137" aria-labelledby="pdf-2202.00137">pdf</a>, <a href="/format/2202.00137" title="Other formats" id="oth-2202.00137" aria-labelledby="oth-2202.00137">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=S%C3%A1nchez,+P+M+S">Pedro Miguel S谩nchez S谩nchez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Celdr%C3%A1n,+A+H">Alberto Huertas Celdr谩n</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schenk,+T">Timo Schenk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Iten,+A+L+B">Adrian Lars Benjamin Iten</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bovet,+G">G茅r么me Bovet</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=P%C3%A9rez,+G+M">Gregorio Mart铆nez P茅rez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stiller,+B">Burkhard Stiller</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2202.00142" title="Abstract" id="2202.00142"> arXiv:2202.00142 </a> [<a href="/pdf/2202.00142" title="Download PDF" id="pdf-2202.00142" aria-labelledby="pdf-2202.00142">pdf</a>, <a href="/format/2202.00142" title="Other formats" id="oth-2202.00142" aria-labelledby="oth-2202.00142">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Higher-Order Language for Markov Kernels and Linear Operators </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=de+Amorim,+P+H+A">Pedro H. Azevedo de Amorim</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Updated title. Accepted at FoSSaCS 2023 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Logic in Computer Science (cs.LO)</span>; Programming Languages (cs.PL) </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/2202.00144" title="Abstract" id="2202.00144"> arXiv:2202.00144 </a> [<a href="/pdf/2202.00144" title="Download PDF" id="pdf-2202.00144" aria-labelledby="pdf-2202.00144">pdf</a>, <a href="/format/2202.00144" title="Other formats" id="oth-2202.00144" aria-labelledby="oth-2202.00144">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Adaptive sampling and domain learning strategy for multivariate function approximation on unknown domains </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Adcock,+B">Ben Adcock</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Cardenas,+J+M">Juan M. Cardenas</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Dexter,+N">Nick Dexter</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Numerical Analysis (math.NA)</span> </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/2202.00145" title="Abstract" id="2202.00145"> arXiv:2202.00145 </a> [<a href="/pdf/2202.00145" title="Download PDF" id="pdf-2202.00145" aria-labelledby="pdf-2202.00145">pdf</a>, <a href="/format/2202.00145" title="Other formats" id="oth-2202.00145" aria-labelledby="oth-2202.00145">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Step-size Adaptation Using Exponentiated Gradient Updates </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Amid,+E">Ehsan Amid</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Anil,+R">Rohan Anil</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fifty,+C">Christopher Fifty</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Warmuth,+M+K">Manfred K. Warmuth</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='item46'>[46]</a> <a href ="/abs/2202.00146" title="Abstract" id="2202.00146"> arXiv:2202.00146 </a> [<a href="/pdf/2202.00146" title="Download PDF" id="pdf-2202.00146" aria-labelledby="pdf-2202.00146">pdf</a>, <a href="/format/2202.00146" title="Other formats" id="oth-2202.00146" aria-labelledby="oth-2202.00146">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kocherzhenko,+A+A">Aleksey A. Kocherzhenko</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kartha,+N+S">Nirmal Sobha Kartha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+T">Tengfei Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hsin-Yi">Hsin-Yi</a> (Jenny)<a href="https://arxiv.org/search/cs?searchtype=author&query=Shih">Shih</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mandic,+M">Marco Mandic</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fuller,+M">Mike Fuller</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Navruzyan,+A">Arshak Navruzyan</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='item47'>[47]</a> <a href ="/abs/2202.00150" title="Abstract" id="2202.00150"> arXiv:2202.00150 </a> [<a href="/pdf/2202.00150" title="Download PDF" id="pdf-2202.00150" aria-labelledby="pdf-2202.00150">pdf</a>, <a href="/format/2202.00150" title="Other formats" id="oth-2202.00150" aria-labelledby="oth-2202.00150">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+L">Liyu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jain,+R">Rahul Jain</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Luo,+H">Haipeng Luo</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='item48'>[48]</a> <a href ="/abs/2202.00151" title="Abstract" id="2202.00151"> arXiv:2202.00151 </a> [<a href="/pdf/2202.00151" title="Download PDF" id="pdf-2202.00151" aria-labelledby="pdf-2202.00151">pdf</a>, <a href="/format/2202.00151" title="Other formats" id="oth-2202.00151" aria-labelledby="oth-2202.00151">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DRS-LIP: Linear Inverted Pendulum Model for Legged Locomotion on Dynamic Rigid Surfaces </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Iqbal,+A">Amir Iqbal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Veer,+S">Sushant Veer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gu,+Y">Yan Gu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 8 figures. Submitted to AIM2022 concurrent submission </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Robotics (cs.RO)</span> </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2202.00153" title="Abstract" id="2202.00153"> arXiv:2202.00153 </a> [<a href="/pdf/2202.00153" title="Download PDF" id="pdf-2202.00153" aria-labelledby="pdf-2202.00153">pdf</a>, <a href="/format/2202.00153" title="Other formats" id="oth-2202.00153" aria-labelledby="oth-2202.00153">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Transformer-based Models of Text Normalization for Speech Applications </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ro,+J+H">Jae Hun Ro</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stahlberg,+F">Felix Stahlberg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+K">Ke Wu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kumar,+S">Shankar Kumar</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/2202.00155" title="Abstract" id="2202.00155"> arXiv:2202.00155 </a> [<a href="/pdf/2202.00155" title="Download PDF" id="pdf-2202.00155" aria-labelledby="pdf-2202.00155">pdf</a>, <a href="/format/2202.00155" title="Other formats" id="oth-2202.00155" aria-labelledby="oth-2202.00155">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fortuitous Forgetting in Connectionist Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+H">Hattie Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vani,+A">Ankit Vani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Larochelle,+H">Hugo Larochelle</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Courville,+A">Aaron Courville</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ICLR Camera Ready </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> ICLR 2022 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE) </div> </div> </dd> </dl> <div class='paging'>Total of 6235 entries : <span>1-50</span> <a href=/list/cs/2022-02?skip=50&show=50>51-100</a> <a href=/list/cs/2022-02?skip=100&show=50>101-150</a> <a href=/list/cs/2022-02?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs/2022-02?skip=6200&show=50>6201-6235</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs/2022-02?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs/2022-02?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs/2022-02?skip=0&show=2000 rel="nofollow"> all</a> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> <a href="https://info.arxiv.org/help/contact.html"> Contact</a> </li> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>subscribe to arXiv mailings</title><desc>Click here to subscribe</desc><path d="M476 3.2L12.5 270.6c-18.1 10.4-15.8 35.6 2.2 43.2L121 358.4l287.3-253.2c5.5-4.9 13.3 2.6 8.6 8.3L176 407v80.5c0 23.6 28.5 32.9 42.5 15.8L282 426l124.6 52.2c14.2 6 30.4-2.9 33-18.2l72-432C515 7.8 493.3-6.8 476 3.2z"/></svg> <a href="https://info.arxiv.org/help/subscribe"> Subscribe</a> </li> </ul> </div> </div> </div>   <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/help/license/index.html">Copyright</a></li> <li><a href="https://info.arxiv.org/help/policies/privacy_policy.html">Privacy Policy</a></li> </ul> </div> <div class="column sorry-app-links"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/help/web_accessibility.html">Web Accessibility Assistance</a></li> <li> <p class="help"> <a class="a11y-main-link" href="https://status.arxiv.org" target="_blank">arXiv Operational Status <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 256 512" class="icon filter-dark_grey" role="presentation"><path d="M224.3 273l-136 136c-9.4 9.4-24.6 9.4-33.9 0l-22.6-22.6c-9.4-9.4-9.4-24.6 0-33.9l96.4-96.4-96.4-96.4c-9.4-9.4-9.4-24.6 0-33.9L54.3 103c9.4-9.4 24.6-9.4 33.9 0l136 136c9.5 9.4 9.5 24.6.1 34z"/></svg></a><br> Get status notifications via <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/email/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg>email</a> or <a class="is-link" href="https://subscribe.sorryapp.com/24846f03/slack/new" target="_blank"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" class="icon filter-black" role="presentation"><path d="M94.12 315.1c0 25.9-21.16 47.06-47.06 47.06S0 341 0 315.1c0-25.9 21.16-47.06 47.06-47.06h47.06v47.06zm23.72 0c0-25.9 21.16-47.06 47.06-47.06s47.06 21.16 47.06 47.06v117.84c0 25.9-21.16 47.06-47.06 47.06s-47.06-21.16-47.06-47.06V315.1zm47.06-188.98c-25.9 0-47.06-21.16-47.06-47.06S139 32 164.9 32s47.06 21.16 47.06 47.06v47.06H164.9zm0 23.72c25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06H47.06C21.16 243.96 0 222.8 0 196.9s21.16-47.06 47.06-47.06H164.9zm188.98 47.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06h-47.06V196.9zm-23.72 0c0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06V79.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06V196.9zM283.1 385.88c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06v-47.06h47.06zm0-23.72c-25.9 0-47.06-21.16-47.06-47.06 0-25.9 21.16-47.06 47.06-47.06h117.84c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06H283.1z"/></svg>slack</a> </p> </li> </ul> </div> </div> </div>   </div> </footer> </div> <script src="/static/base/1.0.1/js/member_acknowledgement.js"></script> </body> </html>

CINXE.COM

Computer Science Feb 2022