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Computer Science Jun 2021
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per page: <a href=/list/cs/2021-06?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs/2021-06?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs/2021-06?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/2106.00001" title="Abstract" id="2106.00001"> arXiv:2106.00001 </a> [<a href="/pdf/2106.00001" title="Download PDF" id="pdf-2106.00001" aria-labelledby="pdf-2106.00001">pdf</a>, <a href="/format/2106.00001" title="Other formats" id="oth-2106.00001" aria-labelledby="oth-2106.00001">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Privately Learning Subspaces </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Singhal,+V">Vikrant Singhal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Steinke,+T">Thomas Steinke</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Cryptography and Security (cs.CR)</span>; Data Structures and Algorithms (cs.DS); Machine Learning (cs.LG); Computation (stat.CO) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2106.00002" title="Abstract" id="2106.00002"> arXiv:2106.00002 </a> [<a href="/pdf/2106.00002" title="Download PDF" id="pdf-2106.00002" aria-labelledby="pdf-2106.00002">pdf</a>, <a href="/format/2106.00002" title="Other formats" id="oth-2106.00002" aria-labelledby="oth-2106.00002">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Analysis and classification of main risk factors causing stroke in Shanxi Province </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+J">Junjie Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+Y">Yiyang Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+J">Jing Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tu,+J">Jiachen Tu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+Y">Yuhui Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+P">Ping He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+H">Huaxiong Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+X">Xiaoshuang Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+S">Shixin Xu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 13 pages, 9 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='item3'>[3]</a> <a href ="/abs/2106.00003" title="Abstract" id="2106.00003"> arXiv:2106.00003 </a> [<a href="/pdf/2106.00003" title="Download PDF" id="pdf-2106.00003" aria-labelledby="pdf-2106.00003">pdf</a>, <a href="/format/2106.00003" title="Other formats" id="oth-2106.00003" aria-labelledby="oth-2106.00003">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hamze,+F">Firas Hamze</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Distributed, Parallel, and Cluster Computing (cs.DC) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2106.00007" title="Abstract" id="2106.00007"> arXiv:2106.00007 </a> [<a href="/pdf/2106.00007" title="Download PDF" id="pdf-2106.00007" aria-labelledby="pdf-2106.00007">pdf</a>, <a href="/format/2106.00007" title="Other formats" id="oth-2106.00007" aria-labelledby="oth-2106.00007">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DikpolaSat Mission: Improvement of Space Flight Performance and Optimal Control Using Trained Deep Neural Network -- Trajectory Controller for Space Objects Collision Avoidance </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ntumba,+M">Manuel Ntumba</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gore,+S">Saurabh Gore</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Awanyo,+J+B">Jean Baptiste Awanyo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 7 pages, 8 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Robotics (cs.RO)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2106.00008" title="Abstract" id="2106.00008"> arXiv:2106.00008 </a> [<a href="/pdf/2106.00008" title="Download PDF" id="pdf-2106.00008" aria-labelledby="pdf-2106.00008">pdf</a>, <a href="/format/2106.00008" title="Other formats" id="oth-2106.00008" aria-labelledby="oth-2106.00008">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robust discovery of partial differential equations in complex situations </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+H">Hao Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+D">Dongxiao Zhang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 20 pages, 8 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Phys. Rev. Research 3, 033270 (2021) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2106.00010" title="Abstract" id="2106.00010"> arXiv:2106.00010 </a> [<a href="/pdf/2106.00010" title="Download PDF" id="pdf-2106.00010" aria-labelledby="pdf-2106.00010">pdf</a>, <a href="/format/2106.00010" title="Other formats" id="oth-2106.00010" aria-labelledby="oth-2106.00010">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multi-Scale Attention Neural Network for Acoustic Echo Cancellation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+L">Lu Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+S">Song Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gong,+Y">Yaguang Gong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+Z">Zhongqin Wu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 3 figures, 4 tables. arXiv admin note: substantial text overlap with <a href="https://arxiv.org/abs/2105.14666" data-arxiv-id="2105.14666" class="link-https">arXiv:2105.14666</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Sound (cs.SD)</span>; Audio and Speech Processing (eess.AS) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2106.00011" title="Abstract" id="2106.00011"> arXiv:2106.00011 </a> [<a href="/pdf/2106.00011" title="Download PDF" id="pdf-2106.00011" aria-labelledby="pdf-2106.00011">pdf</a>, <a href="/format/2106.00011" title="Other formats" id="oth-2106.00011" aria-labelledby="oth-2106.00011">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Constrained Deep Reinforcement Based Functional Split Optimization in Virtualized RANs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Murti,+F+W">Fahri Wisnu Murti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ali,+S">Samad Ali</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Latva-aho,+M">Matti Latva-aho</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This article has been accepted for publication in IEEE Transactions on Wireless Communications </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Networking and Internet Architecture (cs.NI)</span>; Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2106.00012" title="Abstract" id="2106.00012"> arXiv:2106.00012 </a> [<a href="/pdf/2106.00012" title="Download PDF" id="pdf-2106.00012" aria-labelledby="pdf-2106.00012">pdf</a>, <a href="/format/2106.00012" title="Other formats" id="oth-2106.00012" aria-labelledby="oth-2106.00012">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Persistent Homology Captures the Generalization of Neural Networks Without A Validation Set </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Guti%C3%A9rrez-Fandi%C3%B1o,+A">Asier Guti茅rrez-Fandi帽o</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=P%C3%A9rez-Fern%C3%A1ndez,+D">David P茅rez-Fern谩ndez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Armengol-Estap%C3%A9,+J">Jordi Armengol-Estap茅</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Villegas,+M">Marta Villegas</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Algebraic Topology (math.AT) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2106.00014" title="Abstract" id="2106.00014"> arXiv:2106.00014 </a> [<a href="/pdf/2106.00014" title="Download PDF" id="pdf-2106.00014" aria-labelledby="pdf-2106.00014">pdf</a>, <a href="/format/2106.00014" title="Other formats" id="oth-2106.00014" aria-labelledby="oth-2106.00014">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Diffusion Self-Organizing Map on the Hypersphere </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Andrecut,+M">M. Andrecut</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 pages, 4 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Neural and Evolutionary Computing (cs.NE)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2106.00026" title="Abstract" id="2106.00026"> arXiv:2106.00026 </a> [<a href="/pdf/2106.00026" title="Download PDF" id="pdf-2106.00026" aria-labelledby="pdf-2106.00026">pdf</a>, <a href="/format/2106.00026" title="Other formats" id="oth-2106.00026" aria-labelledby="oth-2106.00026">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Machine-Learning Non-Conservative Dynamics for New-Physics Detection </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Z">Ziming Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+B">Bohan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Meng,+Q">Qi Meng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+W">Wei Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tegmark,+M">Max Tegmark</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+T">Tie-Yan Liu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages, 7 figs, 2 tables; typo correction </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Instrumentation and Methods for Astrophysics (astro-ph.IM); General Relativity and Quantum Cosmology (gr-qc); Computational Physics (physics.comp-ph) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2106.00038" title="Abstract" id="2106.00038"> arXiv:2106.00038 </a> [<a href="/pdf/2106.00038" title="Download PDF" id="pdf-2106.00038" aria-labelledby="pdf-2106.00038">pdf</a>, <a href="/format/2106.00038" title="Other formats" id="oth-2106.00038" aria-labelledby="oth-2106.00038">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lou,+Q">Qian Lou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+L">Lei Jiang</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> The Thirty-eighth International Conference on Machine Learning 2021 </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='item12'>[12]</a> <a href ="/abs/2106.00041" title="Abstract" id="2106.00041"> arXiv:2106.00041 </a> [<a href="/pdf/2106.00041" title="Download PDF" id="pdf-2106.00041" aria-labelledby="pdf-2106.00041">pdf</a>, <a href="/format/2106.00041" title="Other formats" id="oth-2106.00041" aria-labelledby="oth-2106.00041">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Grammatical Approach for Distributed Business Process Management using Structured and Cooperatively Edited Mobile Artifacts </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ndadji,+M+M+Z">Milliam Maxime Zekeng Ndadji</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Software Engineering (cs.SE)</span>; Formal Languages and Automata Theory (cs.FL) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2106.00042" title="Abstract" id="2106.00042"> arXiv:2106.00042 </a> [<a href="/pdf/2106.00042" title="Download PDF" id="pdf-2106.00042" aria-labelledby="pdf-2106.00042">pdf</a>, <a href="/format/2106.00042" title="Other formats" id="oth-2106.00042" aria-labelledby="oth-2106.00042">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A study on the plasticity of neural networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Berariu,+T">Tudor Berariu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Czarnecki,+W">Wojciech Czarnecki</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=De,+S">Soham De</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bornschein,+J">Jorg Bornschein</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Smith,+S">Samuel Smith</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pascanu,+R">Razvan Pascanu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Clopath,+C">Claudia Clopath</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/2106.00047" title="Abstract" id="2106.00047"> arXiv:2106.00047 </a> [<a href="/pdf/2106.00047" title="Download PDF" id="pdf-2106.00047" aria-labelledby="pdf-2106.00047">pdf</a>, <a href="/format/2106.00047" title="Other formats" id="oth-2106.00047" aria-labelledby="oth-2106.00047">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning and Generalization in RNNs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Panigrahi,+A">Abhishek Panigrahi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Goyal,+N">Navin Goyal</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/2106.00050" title="Abstract" id="2106.00050"> arXiv:2106.00050 </a> [<a href="/pdf/2106.00050" title="Download PDF" id="pdf-2106.00050" aria-labelledby="pdf-2106.00050">pdf</a>, <a href="/format/2106.00050" title="Other formats" id="oth-2106.00050" aria-labelledby="oth-2106.00050">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Continual 3D Convolutional Neural Networks for Real-time Processing of Videos </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hedegaard,+L">Lukas Hedegaard</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Iosifidis,+A">Alexandros Iosifidis</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 pages, 9 figures, 7 tables </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> ECCV 2022 </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='item16'>[16]</a> <a href ="/abs/2106.00055" title="Abstract" id="2106.00055"> arXiv:2106.00055 </a> [<a href="/pdf/2106.00055" title="Download PDF" id="pdf-2106.00055" aria-labelledby="pdf-2106.00055">pdf</a>, <a href="/format/2106.00055" title="Other formats" id="oth-2106.00055" aria-labelledby="oth-2106.00055">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> More than just Frequency? Demasking Unsupervised Hypernymy Prediction Methods </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bott,+T">Thomas Bott</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Schlechtweg,+D">Dominik Schlechtweg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Walde,+S+S+i">Sabine Schulte im Walde</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ACL Findings, 5 pages </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/2106.00058" title="Abstract" id="2106.00058"> arXiv:2106.00058 </a> [<a href="/pdf/2106.00058" title="Download PDF" id="pdf-2106.00058" aria-labelledby="pdf-2106.00058">pdf</a>, <a href="/format/2106.00058" title="Other formats" id="oth-2106.00058" aria-labelledby="oth-2106.00058">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Stable and Interpretable Unrolled Dictionary Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tolooshams,+B">Bahareh Tolooshams</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ba,+D">Demba Ba</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published in Transactions on Machine Learning Research (TMLR) (08/2022) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2106.00062" title="Abstract" id="2106.00062"> arXiv:2106.00062 </a> [<a href="/pdf/2106.00062" title="Download PDF" id="pdf-2106.00062" aria-labelledby="pdf-2106.00062">pdf</a>, <a href="/format/2106.00062" title="Other formats" id="oth-2106.00062" aria-labelledby="oth-2106.00062">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Controllable Gradient Item Retrieval </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+H">Haonan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+C">Chang 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=Yang,+H">Hongxia Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+J">Jingrui He</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by The International World Wide Web Conference (WWW), 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Information Retrieval (cs.IR)</span> </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2106.00063" title="Abstract" id="2106.00063"> arXiv:2106.00063 </a> [<a href="/pdf/2106.00063" title="Download PDF" id="pdf-2106.00063" aria-labelledby="pdf-2106.00063">pdf</a>, <a href="/format/2106.00063" title="Other formats" id="oth-2106.00063" aria-labelledby="oth-2106.00063">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Living mycelium composites discern weights </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Adamatzky,+A">Andrew Adamatzky</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gandia,+A">Antoni Gandia</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Emerging Technologies (cs.ET)</span> </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/2106.00066" title="Abstract" id="2106.00066"> arXiv:2106.00066 </a> [<a href="/pdf/2106.00066" title="Download PDF" id="pdf-2106.00066" aria-labelledby="pdf-2106.00066">pdf</a>, <a href="/format/2106.00066" title="Other formats" id="oth-2106.00066" aria-labelledby="oth-2106.00066">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Energy and Network Aware Workload Management for Geographically Distributed Data Centers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hogade,+N">Ninad Hogade</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pasricha,+S">Sudeep Pasricha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Siegel,+H+J">Howard Jay Siegel</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Distributed, Parallel, and Cluster Computing (cs.DC)</span>; Computer Science and Game Theory (cs.GT); Networking and Internet Architecture (cs.NI) </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/2106.00073" title="Abstract" id="2106.00073"> arXiv:2106.00073 </a> [<a href="/pdf/2106.00073" title="Download PDF" id="pdf-2106.00073" aria-labelledby="pdf-2106.00073">pdf</a>, <a href="/format/2106.00073" title="Other formats" id="oth-2106.00073" aria-labelledby="oth-2106.00073">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GRAVITAS: Graphical Reticulated Attack Vectors for Internet-of-Things Aggregate Security </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Brown,+J">Jacob Brown</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saha,+T">Tanujay Saha</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jha,+N+K">Niraj K. Jha</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This article has been published in IEEE Transactions on Emerging Topics in Computing, 2021 </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); Networking and Internet Architecture (cs.NI) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2106.00076" title="Abstract" id="2106.00076"> arXiv:2106.00076 </a> [<a href="/pdf/2106.00076" title="Download PDF" id="pdf-2106.00076" aria-labelledby="pdf-2106.00076">pdf</a>, <a href="/format/2106.00076" title="Other formats" id="oth-2106.00076" aria-labelledby="oth-2106.00076">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Cygert,+S">Sebastian Cygert</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wr%C3%B3blewski,+B">Bart艂omiej Wr贸blewski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wo%C5%BAniak,+K">Karol Wo藕niak</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=S%C5%82owi%C5%84ski,+R">Rados艂aw S艂owi艅ski</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Czy%C5%BCewski,+A">Andrzej Czy偶ewski</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> International Joint Conference on Neural Networks 2021, <a href="https://ieeexplore.ieee.org/document/9533330" 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> </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2106.00077" title="Abstract" id="2106.00077"> arXiv:2106.00077 </a> [<a href="/pdf/2106.00077" title="Download PDF" id="pdf-2106.00077" aria-labelledby="pdf-2106.00077">pdf</a>, <a href="/format/2106.00077" title="Other formats" id="oth-2106.00077" aria-labelledby="oth-2106.00077">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Automating Visualization Quality Assessment: a Case Study in Higher Education </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Holliman,+N+S">Nicolas Steven Holliman</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Human-Computer Interaction (cs.HC)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2106.00083" title="Abstract" id="2106.00083"> arXiv:2106.00083 </a> [<a href="/pdf/2106.00083" title="Download PDF" id="pdf-2106.00083" aria-labelledby="pdf-2106.00083">pdf</a>, <a href="/format/2106.00083" title="Other formats" id="oth-2106.00083" aria-labelledby="oth-2106.00083">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Composing Networks of Automated Market Makers </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Engel,+D">Daniel Engel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Herlihy,+M">Maurice Herlihy</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Distributed, Parallel, and Cluster Computing (cs.DC)</span>; Multiagent Systems (cs.MA) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2106.00085" title="Abstract" id="2106.00085"> arXiv:2106.00085 </a> [<a href="/pdf/2106.00085" title="Download PDF" id="pdf-2106.00085" aria-labelledby="pdf-2106.00085">pdf</a>, <a href="/format/2106.00085" title="Other formats" id="oth-2106.00085" aria-labelledby="oth-2106.00085">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Language Model Evaluation Beyond Perplexity </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Meister,+C">Clara Meister</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cotterell,+R">Ryan Cotterell</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ACL 2021 </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='item26'>[26]</a> <a href ="/abs/2106.00089" title="Abstract" id="2106.00089"> arXiv:2106.00089 </a> [<a href="/pdf/2106.00089" title="Download PDF" id="pdf-2106.00089" aria-labelledby="pdf-2106.00089">pdf</a>, <a href="/format/2106.00089" title="Other formats" id="oth-2106.00089" aria-labelledby="oth-2106.00089">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Node-Variant Graph Filters in Graph Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Gama,+F">Fernando Gama</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Anderson,+B+G">Brendon G. Anderson</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sojoudi,+S">Somayeh Sojoudi</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='item27'>[27]</a> <a href ="/abs/2106.00090" title="Abstract" id="2106.00090"> arXiv:2106.00090 </a> [<a href="/pdf/2106.00090" title="Download PDF" id="pdf-2106.00090" aria-labelledby="pdf-2106.00090">pdf</a>, <a href="/format/2106.00090" title="Other formats" id="oth-2106.00090" aria-labelledby="oth-2106.00090">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Z">Zhikun Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yuanpeng Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hong,+Y">Yuan Hong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Meng,+J">Jinwen Meng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+J">Jianguo Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zheng,+S">Shusen Zheng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+X">Xiao Xu</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='item28'>[28]</a> <a href ="/abs/2106.00091" title="Abstract" id="2106.00091"> arXiv:2106.00091 </a> [<a href="/pdf/2106.00091" title="Download PDF" id="pdf-2106.00091" aria-labelledby="pdf-2106.00091">pdf</a>, <a href="/format/2106.00091" title="Other formats" id="oth-2106.00091" aria-labelledby="oth-2106.00091">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Algorithms for Multiwinner Elections and the Chamberlin-Courant Rule </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Munagala,+K">Kamesh Munagala</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shen,+Z">Zeyu Shen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+K">Kangning Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by the Twenty-Second ACM Conference on Economics and Computation (EC 2021) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Science and Game Theory (cs.GT)</span>; Data Structures and Algorithms (cs.DS); Theoretical Economics (econ.TH) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2106.00092" title="Abstract" id="2106.00092"> arXiv:2106.00092 </a> [<a href="/pdf/2106.00092" title="Download PDF" id="pdf-2106.00092" aria-labelledby="pdf-2106.00092">pdf</a>, <a href="/format/2106.00092" title="Other formats" id="oth-2106.00092" aria-labelledby="oth-2106.00092">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chakrabarti,+K">Kushal Chakrabarti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chopra,+N">Nikhil Chopra</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Updates: The parameter condition of Adam in Theorem 2 has been relaxed and the proof has been updated accordingly. Experimental results on logistic regression model have been included. Conference: Accepted for presentation in the 2021 60th IEEE Conference on Decision and Control (CDC) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Systems and Control (eess.SY); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2106.00093" title="Abstract" id="2106.00093"> arXiv:2106.00093 </a> [<a href="/pdf/2106.00093" title="Download PDF" id="pdf-2106.00093" aria-labelledby="pdf-2106.00093">pdf</a>, <a href="/format/2106.00093" title="Other formats" id="oth-2106.00093" aria-labelledby="oth-2106.00093">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Approximate polymorphisms </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chase,+G">Gilad Chase</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Filmus,+Y">Yuval Filmus</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Minzer,+D">Dor Minzer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mossel,+E">Elchanan Mossel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Saurabh,+N">Nitin Saurabh</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 43 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Discrete Mathematics (cs.DM)</span>; Combinatorics (math.CO) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/2106.00099" title="Abstract" id="2106.00099"> arXiv:2106.00099 </a> [<a href="/pdf/2106.00099" title="Download PDF" id="pdf-2106.00099" aria-labelledby="pdf-2106.00099">pdf</a>, <a href="/format/2106.00099" title="Other formats" id="oth-2106.00099" aria-labelledby="oth-2106.00099">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Satija,+H">Harsh Satija</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thomas,+P+S">Philip S. Thomas</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pineau,+J">Joelle Pineau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Laroche,+R">Romain Laroche</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='item32'>[32]</a> <a href ="/abs/2106.00102" title="Abstract" id="2106.00102"> arXiv:2106.00102 </a> [<a href="/pdf/2106.00102" title="Download PDF" id="pdf-2106.00102" aria-labelledby="pdf-2106.00102">pdf</a>, <a href="/format/2106.00102" title="Other formats" id="oth-2106.00102" aria-labelledby="oth-2106.00102">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Cold-start Problem: Minimal Users' Activity Estimation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Visnovsky,+J">Juraj Visnovsky</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kassak,+O">Ondrej Kassak</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kompan,+M">Michal Kompan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bielikova,+M">Maria Bielikova</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 1st Workshop on Recommender Systems for Television and online Video (RecSysTV) in conjunction with 8th ACM Conference on Recommender Systems, 2014 </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 1st Workshop on Recommender Systems for Television and online Video (RecSysTV) in conjunction with 8th ACM Conference on Recommender Systems, 2014 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Information Retrieval (cs.IR)</span> </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2106.00104" title="Abstract" id="2106.00104"> arXiv:2106.00104 </a> [<a href="/pdf/2106.00104" title="Download PDF" id="pdf-2106.00104" aria-labelledby="pdf-2106.00104">pdf</a>, <a href="/format/2106.00104" title="Other formats" id="oth-2106.00104" aria-labelledby="oth-2106.00104">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Text Summarization with Latent Queries </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+Y">Yumo Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lapata,+M">Mirella Lapata</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation and Language (cs.CL)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/2106.00107" title="Abstract" id="2106.00107"> arXiv:2106.00107 </a> [<a href="/pdf/2106.00107" title="Download PDF" id="pdf-2106.00107" aria-labelledby="pdf-2106.00107">pdf</a>, <a href="/format/2106.00107" title="Other formats" id="oth-2106.00107" aria-labelledby="oth-2106.00107">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> 3D map creation using crowdsourced GNSS data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lines,+T">Terence Lines</a> (1), <a href="https://arxiv.org/search/cs?searchtype=author&query=Basiri,+A">Ana Basiri</a> (1) ((1) School of Geographical and Earth Sciences, University of Glasgow)</div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 pages with 11 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Robotics (cs.RO)</span>; Computer Vision and Pattern Recognition (cs.CV); Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2106.00109" title="Abstract" id="2106.00109"> arXiv:2106.00109 </a> [<a href="/pdf/2106.00109" title="Download PDF" id="pdf-2106.00109" aria-labelledby="pdf-2106.00109">pdf</a>, <a href="/format/2106.00109" title="Other formats" id="oth-2106.00109" aria-labelledby="oth-2106.00109">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Equilibrium Computation of Generalized Nash Games: A New Lagrangian-Based Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+J+G">Jong Gwang Kim</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Extended version of the EC'21 conference paper </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of the 22nd ACM Conference on Economics and Computation (EC'21), 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computer Science and Game Theory (cs.GT)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2106.00110" title="Abstract" id="2106.00110"> arXiv:2106.00110 </a> [<a href="/pdf/2106.00110" title="Download PDF" id="pdf-2106.00110" aria-labelledby="pdf-2106.00110">pdf</a>, <a href="/format/2106.00110" title="Other formats" id="oth-2106.00110" aria-labelledby="oth-2106.00110">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Methodology for Exploring Deep Convolutional Features in Relation to Hand-Crafted Features with an Application to Music Audio Modeling </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Yanchenko,+A+K">Anna K. Yanchenko</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Soltani,+M">Mohammadreza Soltani</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ravier,+R+J">Robert J. Ravier</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mukherjee,+S">Sayan Mukherjee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tarokh,+V">Vahid Tarokh</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Code available at <a href="https://github.com/aky4wn/convolutions-for-music-audio" 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">Sound (cs.SD)</span>; Machine Learning (cs.LG); Audio and Speech Processing (eess.AS) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2106.00115" title="Abstract" id="2106.00115"> arXiv:2106.00115 </a> [<a href="/pdf/2106.00115" title="Download PDF" id="pdf-2106.00115" aria-labelledby="pdf-2106.00115">pdf</a>, <a href="/format/2106.00115" title="Other formats" id="oth-2106.00115" aria-labelledby="oth-2106.00115">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fine-grained Generalization Analysis of Structured Output Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mustafa,+W">Waleed Mustafa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lei,+Y">Yunwen Lei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ledent,+A">Antoine Ledent</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kloft,+M">Marius Kloft</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appearn in IJCAI 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2106.00116" title="Abstract" id="2106.00116"> arXiv:2106.00116 </a> [<a href="/pdf/2106.00116" title="Download PDF" id="pdf-2106.00116" aria-labelledby="pdf-2106.00116">pdf</a>, <a href="/format/2106.00116" title="Other formats" id="oth-2106.00116" aria-labelledby="oth-2106.00116">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest Images </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Cherti,+M">Mehdi Cherti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jitsev,+J">Jenia Jitsev</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Short version published in MedNeurIPS 2021. Long version published in IJCNN 2022. Code: <a href="https://github.com/SLAMPAI/large-scale-pretraining-transfer" rel="external noopener nofollow" class="link-external link-https">this https URL</a> </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 2022 International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-9 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2106.00120" title="Abstract" id="2106.00120"> arXiv:2106.00120 </a> [<a href="/pdf/2106.00120" title="Download PDF" id="pdf-2106.00120" aria-labelledby="pdf-2106.00120">pdf</a>, <a href="/format/2106.00120" title="Other formats" id="oth-2106.00120" aria-labelledby="oth-2106.00120">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chang,+D+T">Daniel T. Chang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> arXiv admin note: text overlap with <a href="https://arxiv.org/abs/1811.06622" data-arxiv-id="1811.06622" class="link-https">arXiv:1811.06622</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='item40'>[40]</a> <a href ="/abs/2106.00122" title="Abstract" id="2106.00122"> arXiv:2106.00122 </a> [<a href="/pdf/2106.00122" title="Download PDF" id="pdf-2106.00122" aria-labelledby="pdf-2106.00122">pdf</a>, <a href="/format/2106.00122" title="Other formats" id="oth-2106.00122" aria-labelledby="oth-2106.00122">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Suppressing the endemic equilibrium in SIS epidemics: A state dependent approach </div> <div class='list-authors'><a href="https://arxiv.org/search/eess?searchtype=author&query=Wang,+Y">Yuan Wang</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Gracy,+S">Sebin Gracy</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Ishii,+H">Hideaki Ishii</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Johansson,+K+H">Karl Henrik Johansson</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='item41'>[41]</a> <a href ="/abs/2106.00123" title="Abstract" id="2106.00123"> arXiv:2106.00123 </a> [<a href="/pdf/2106.00123" title="Download PDF" id="pdf-2106.00123" aria-labelledby="pdf-2106.00123">pdf</a>, <a href="/format/2106.00123" title="Other formats" id="oth-2106.00123" aria-labelledby="oth-2106.00123">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Pricope,+T">Tidor-Vlad Pricope</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Trading and Market Microstructure (q-fin.TR) </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2106.00124" title="Abstract" id="2106.00124"> arXiv:2106.00124 </a> [<a href="/pdf/2106.00124" title="Download PDF" id="pdf-2106.00124" aria-labelledby="pdf-2106.00124">pdf</a>, <a href="/format/2106.00124" title="Other formats" id="oth-2106.00124" aria-labelledby="oth-2106.00124">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multidimensional Included and Excluded Sums </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+H">Helen Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fraser,+S">Sean Fraser</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Leiserson,+C+E">Charles E. Leiserson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 18 pages, short version to appear in ACDA 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Data Structures and Algorithms (cs.DS)</span> </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2106.00127" title="Abstract" id="2106.00127"> arXiv:2106.00127 </a> [<a href="/pdf/2106.00127" title="Download PDF" id="pdf-2106.00127" aria-labelledby="pdf-2106.00127">pdf</a>, <a href="/format/2106.00127" title="Other formats" id="oth-2106.00127" aria-labelledby="oth-2106.00127">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Integer-Only Neural Network Quantization Scheme Based on Shift-Batch-Normalization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+Q">Qingyu Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yuan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cui,+X">Xiaoxin Cui</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='item44'>[44]</a> <a href ="/abs/2106.00130" title="Abstract" id="2106.00130"> arXiv:2106.00130 </a> [<a href="/pdf/2106.00130" title="Download PDF" id="pdf-2106.00130" aria-labelledby="pdf-2106.00130">pdf</a>, <a href="/format/2106.00130" title="Other formats" id="oth-2106.00130" aria-labelledby="oth-2106.00130">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Meng,+R">Rui Meng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thaker,+K">Khushboo Thaker</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+L">Lei Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dong,+Y">Yue Dong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yuan,+X">Xingdi Yuan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+T">Tong Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+D">Daqing He</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at ACL2021 </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='item45'>[45]</a> <a href ="/abs/2106.00131" title="Abstract" id="2106.00131"> arXiv:2106.00131 </a> [<a href="/pdf/2106.00131" title="Download PDF" id="pdf-2106.00131" aria-labelledby="pdf-2106.00131">pdf</a>, <a href="/format/2106.00131" title="Other formats" id="oth-2106.00131" aria-labelledby="oth-2106.00131">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Tao,+Y">Yaling Tao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Takagi,+K">Kentaro Takagi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nakata,+K">Kouta Nakata</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, ICLR2021 </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='item46'>[46]</a> <a href ="/abs/2106.00132" title="Abstract" id="2106.00132"> arXiv:2106.00132 </a> [<a href="/pdf/2106.00132" title="Download PDF" id="pdf-2106.00132" aria-labelledby="pdf-2106.00132">pdf</a>, <a href="/format/2106.00132" title="Other formats" id="oth-2106.00132" aria-labelledby="oth-2106.00132">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Fast Sampling of Diffusion Probabilistic Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Kong,+Z">Zhifeng Kong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ping,+W">Wei Ping</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Code is released </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/2106.00133" title="Abstract" id="2106.00133"> arXiv:2106.00133 </a> [<a href="/pdf/2106.00133" title="Download PDF" id="pdf-2106.00133" aria-labelledby="pdf-2106.00133">pdf</a>, <a href="/format/2106.00133" title="Other formats" id="oth-2106.00133" aria-labelledby="oth-2106.00133">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shvo,+M">Maayan Shvo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+Z">Zhiming Hu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Icarte,+R+T">Rodrigo Toro Icarte</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mohomed,+I">Iqbal Mohomed</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jepson,+A">Allan Jepson</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=McIlraith,+S+A">Sheila A. McIlraith</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Artificial Intelligence (cs.AI)</span> </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/2106.00134" title="Abstract" id="2106.00134"> arXiv:2106.00134 </a> [<a href="/pdf/2106.00134" title="Download PDF" id="pdf-2106.00134" aria-labelledby="pdf-2106.00134">pdf</a>, <a href="/format/2106.00134" title="Other formats" id="oth-2106.00134" aria-labelledby="oth-2106.00134">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GANs Can Play Lottery Tickets Too </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+X">Xuxi Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Z">Zhenyu Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sui,+Y">Yongduo Sui</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+T">Tianlong Chen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2106.00135" title="Abstract" id="2106.00135"> arXiv:2106.00135 </a> [<a href="/pdf/2106.00135" title="Download PDF" id="pdf-2106.00135" aria-labelledby="pdf-2106.00135">pdf</a>, <a href="/format/2106.00135" title="Other formats" id="oth-2106.00135" aria-labelledby="oth-2106.00135">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Assessing the Impacts of Nonideal Communications on Distributed Optimal Power Flow Algorithms </div> <div class='list-authors'><a href="https://arxiv.org/search/eess?searchtype=author&query=Alkhraijah,+M">Mohannad Alkhraijah</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Menendez,+C">Carlos Menendez</a>, <a href="https://arxiv.org/search/eess?searchtype=author&query=Molzahn,+D+K">Daniel K. Molzahn</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages with 21 figures </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='item50'>[50]</a> <a href ="/abs/2106.00136" title="Abstract" id="2106.00136"> arXiv:2106.00136 </a> [<a href="/pdf/2106.00136" title="Download PDF" id="pdf-2106.00136" aria-labelledby="pdf-2106.00136">pdf</a>, <a href="/format/2106.00136" title="Other formats" id="oth-2106.00136" aria-labelledby="oth-2106.00136">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning </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=Mao,+L">Lei Mao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Makoviychuk,+V">Viktor Makoviychuk</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Garg,+A">Animesh Garg</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kossaifi,+J">Jean Kossaifi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Whiteson,+S">Shimon Whiteson</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhu,+Y">Yuke Zhu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Anandkumar,+A">Animashree Anandkumar</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 38th International Conference on Machine Learning, PMLR 139, 2021 </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 7561 entries : <span>1-50</span> <a href=/list/cs/2021-06?skip=50&show=50>51-100</a> <a href=/list/cs/2021-06?skip=100&show=50>101-150</a> <a href=/list/cs/2021-06?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs/2021-06?skip=7550&show=50>7551-7561</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs/2021-06?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs/2021-06?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs/2021-06?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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