Statistics Oct 2018

<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Oct 2018</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" 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href=/list/stat/2018-10?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2018-10?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2018-10?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1810.00004" title="Abstract" id="1810.00004"> arXiv:1810.00004 </a> [<a href="/pdf/1810.00004" title="Download PDF" id="pdf-1810.00004" aria-labelledby="pdf-1810.00004">pdf</a>, <a href="/format/1810.00004" title="Other formats" id="oth-1810.00004" aria-labelledby="oth-1810.00004">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fluctuation-dissipation relations for stochastic gradient descent </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yaida,+S">Sho Yaida</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, 6 figures; v2: final version accepted at ICLR 2019, with derivations/assumptions clarified and Adam/AMSGrad experiments added </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/1810.00042" title="Abstract" id="1810.00042"> arXiv:1810.00042 </a> [<a href="/pdf/1810.00042" title="Download PDF" id="pdf-1810.00042" aria-labelledby="pdf-1810.00042">pdf</a>, <a href="/format/1810.00042" title="Other formats" id="oth-1810.00042" aria-labelledby="oth-1810.00042">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Semiparametric efficient estimation of structural nested mean models with irregularly spaced observations </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+S">Shu Yang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/1810.00113" title="Abstract" id="1810.00113"> arXiv:1810.00113 </a> [<a href="/pdf/1810.00113" title="Download PDF" id="pdf-1810.00113" aria-labelledby="pdf-1810.00113">pdf</a>, <a href="/format/1810.00113" title="Other formats" id="oth-1810.00113" aria-labelledby="oth-1810.00113">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Predicting the Generalization Gap in Deep Networks with Margin Distributions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Jiang,+Y">Yiding Jiang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Krishnan,+D">Dilip Krishnan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mobahi,+H">Hossein Mobahi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bengio,+S">Samy Bengio</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published in ICLR 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/1810.00116" title="Abstract" id="1810.00116"> arXiv:1810.00116 </a> [<a href="/pdf/1810.00116" title="Download PDF" id="pdf-1810.00116" aria-labelledby="pdf-1810.00116">pdf</a>, <a href="/format/1810.00116" title="Other formats" id="oth-1810.00116" aria-labelledby="oth-1810.00116">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improved Gradient-Based Optimization Over Discrete Distributions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Andriyash,+E">Evgeny Andriyash</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vahdat,+A">Arash Vahdat</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Macready,+B">Bill Macready</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/1810.00117" title="Abstract" id="1810.00117"> arXiv:1810.00117 </a> [<a href="/pdf/1810.00117" title="Download PDF" id="pdf-1810.00117" aria-labelledby="pdf-1810.00117">pdf</a>, <a href="/format/1810.00117" title="Other formats" id="oth-1810.00117" aria-labelledby="oth-1810.00117">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hocking,+T+D">Toby Dylan Hocking</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rigaill,+G">Guillem Rigaill</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fearnhead,+P">Paul Fearnhead</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bourque,+G">Guillaume Bourque</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/1810.00118" title="Abstract" id="1810.00118"> arXiv:1810.00118 </a> [<a href="/pdf/1810.00118" title="Download PDF" id="pdf-1810.00118" aria-labelledby="pdf-1810.00118">pdf</a>, <a href="/format/1810.00118" title="Other formats" id="oth-1810.00118" aria-labelledby="oth-1810.00118">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multilevel Optimal Transport: a Fast Approximation of Wasserstein-1 distances </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+J">Jialin Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yin,+W">Wotao Yin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+W">Wuchen Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chow,+Y+T">Yat Tin Chow</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/1810.00121" title="Abstract" id="1810.00121"> arXiv:1810.00121 </a> [<a href="/pdf/1810.00121" title="Download PDF" id="pdf-1810.00121" aria-labelledby="pdf-1810.00121">pdf</a>, <a href="/format/1810.00121" title="Other formats" id="oth-1810.00121" aria-labelledby="oth-1810.00121">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Discovering Interactions Using Covariate Informed Random Partition Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Page,+G+L">Garritt L. Page</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Quintana,+F+A">Fernando A. Quintana</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rosner,+G+L">Gary L. Rosner</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 29 pages, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/1810.00141" title="Abstract" id="1810.00141"> arXiv:1810.00141 </a> [<a href="/pdf/1810.00141" title="Download PDF" id="pdf-1810.00141" aria-labelledby="pdf-1810.00141">pdf</a>, <a href="/format/1810.00141" title="Other formats" id="oth-1810.00141" aria-labelledby="oth-1810.00141">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neuronized Priors for Bayesian Sparse Linear Regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Shin,+M">Minsuk Shin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+J+S">Jun S Liu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/1810.00210" title="Abstract" id="1810.00210"> arXiv:1810.00210 </a> [<a href="/pdf/1810.00210" title="Download PDF" id="pdf-1810.00210" aria-labelledby="pdf-1810.00210">pdf</a>, <a href="/format/1810.00210" title="Other formats" id="oth-1810.00210" aria-labelledby="oth-1810.00210">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Which country epitomizes the world? A study from the perspective of demographic composition </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yoshida,+T">Takahiro Yoshida</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Er-Rbib,+R">Rim Er-Rbib</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tsutsumi,+M">Morito Tsutsumi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/1810.00216" title="Abstract" id="1810.00216"> arXiv:1810.00216 </a> [<a href="/pdf/1810.00216" title="Download PDF" id="pdf-1810.00216" aria-labelledby="pdf-1810.00216">pdf</a>, <a href="/format/1810.00216" title="Other formats" id="oth-1810.00216" aria-labelledby="oth-1810.00216">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Parameter Estimation for the Single-Look $\mathcal{G}^0$ Distribution </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chan,+D">D茅bora Chan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rey,+A">Andrea Rey</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gambini,+J">Juliana Gambini</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Frery,+A+C">Alejandro C. Frery</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Computer Vision and Pattern Recognition (cs.CV) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/1810.00223" title="Abstract" id="1810.00223"> arXiv:1810.00223 </a> [<a href="/pdf/1810.00223" title="Download PDF" id="pdf-1810.00223" aria-labelledby="pdf-1810.00223">pdf</a>, <a href="/format/1810.00223" title="Other formats" id="oth-1810.00223" aria-labelledby="oth-1810.00223">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generalized Multichannel Variational Autoencoder for Underdetermined Source Separation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Seki,+S">Shogo Seki</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kameoka,+H">Hirokazu Kameoka</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+L">Li Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Toda,+T">Tomoki Toda</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Takeda,+K">Kazuya Takeda</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Sound (cs.SD); Audio and Speech Processing (eess.AS) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/1810.00274" title="Abstract" id="1810.00274"> arXiv:1810.00274 </a> [<a href="/pdf/1810.00274" title="Download PDF" id="pdf-1810.00274" aria-labelledby="pdf-1810.00274">pdf</a>, <a href="/format/1810.00274" title="Other formats" id="oth-1810.00274" aria-labelledby="oth-1810.00274">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian network marker selection via the thresholded graph Laplacian Gaussian prior </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Cai,+Q">Qingpo Cai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kang,+J">Jian Kang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yu,+T">Tianwei Yu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/1810.00289" title="Abstract" id="1810.00289"> arXiv:1810.00289 </a> [<a href="/pdf/1810.00289" title="Download PDF" id="pdf-1810.00289" aria-labelledby="pdf-1810.00289">pdf</a>, <a href="/format/1810.00289" title="Other formats" id="oth-1810.00289" aria-labelledby="oth-1810.00289">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Sheet of Maple to Compute Second-Order Edgeworth Expansions and Related Quantities of any Function of the Mean of an iid Sample of an Absolutely Continuous Distribution </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bertrand,+F">F. Bertrand</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Maumy-Bertrand,+M">M. Maumy-Bertrand</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 20 pages, 8 figures, code snippet </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/1810.00315" title="Abstract" id="1810.00315"> arXiv:1810.00315 </a> [<a href="/pdf/1810.00315" title="Download PDF" id="pdf-1810.00315" aria-labelledby="pdf-1810.00315">pdf</a>, <a href="/format/1810.00315" title="Other formats" id="oth-1810.00315" aria-labelledby="oth-1810.00315">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Convex Relaxation Methods for Community Detection </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Li,+X">Xiaodong Li</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Chen,+Y">Yudong Chen</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Xu,+J">Jiaming Xu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Social and Information Networks (cs.SI); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/1810.00363" title="Abstract" id="1810.00363"> arXiv:1810.00363 </a> [<a href="/pdf/1810.00363" title="Download PDF" id="pdf-1810.00363" aria-labelledby="pdf-1810.00363">pdf</a>, <a href="/format/1810.00363" title="Other formats" id="oth-1810.00363" aria-labelledby="oth-1810.00363">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Kernel Perspective for Regularizing Deep Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bietti,+A">Alberto Bietti</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mialon,+G">Gr茅goire Mialon</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+D">Dexiong Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mairal,+J">Julien Mairal</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ICML </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/1810.00368" title="Abstract" id="1810.00368"> arXiv:1810.00368 </a> [<a href="/pdf/1810.00368" title="Download PDF" id="pdf-1810.00368" aria-labelledby="pdf-1810.00368">pdf</a>, <a href="/format/1810.00368" title="Other formats" id="oth-1810.00368" aria-labelledby="oth-1810.00368">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep Quality-Value (DQV) Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Sabatelli,+M">Matthia Sabatelli</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Louppe,+G">Gilles Louppe</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Geurts,+P">Pierre Geurts</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wiering,+M+A">Marco A. Wiering</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/1810.00412" title="Abstract" id="1810.00412"> arXiv:1810.00412 </a> [<a href="/pdf/1810.00412" title="Download PDF" id="pdf-1810.00412" aria-labelledby="pdf-1810.00412">pdf</a>, <a href="/format/1810.00412" title="Other formats" id="oth-1810.00412" aria-labelledby="oth-1810.00412">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Distributed linear regression by averaging </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Dobriban,+E">Edgar Dobriban</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Sheng,+Y">Yue Sheng</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Fixing a typo </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Ann. Statist. 49(2): 918-943 (April 2021) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Computation (stat.CO); Methodology (stat.ME); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/1810.00440" title="Abstract" id="1810.00440"> arXiv:1810.00440 </a> [<a href="/pdf/1810.00440" title="Download PDF" id="pdf-1810.00440" aria-labelledby="pdf-1810.00440">pdf</a>, <a href="/format/1810.00440" title="Other formats" id="oth-1810.00440" aria-labelledby="oth-1810.00440">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Havasi,+M">Marton Havasi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Peharz,+R">Robert Peharz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hern%C3%A1ndez-Lobato,+J+M">Jos茅 Miguel Hern谩ndez-Lobato</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Under review as a conference paper at ICLR 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/1810.00514" title="Abstract" id="1810.00514"> arXiv:1810.00514 </a> [<a href="/pdf/1810.00514" title="Download PDF" id="pdf-1810.00514" aria-labelledby="pdf-1810.00514">pdf</a>, <a href="/format/1810.00514" title="Other formats" id="oth-1810.00514" aria-labelledby="oth-1810.00514">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Investigating Spatial Error Structures in Continuous Raster Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tsutsumida,+N">Narumasa Tsutsumida</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rodr%C3%ADguez-Veiga,+P">Pedro Rodr铆guez-Veiga</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Harris,+P">Paul Harris</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Balzter,+H">Heiko Balzter</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Comber,+A">Alexis Comber</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This version of manuscript has been accepted for publication in International Journal of Applied Earth Observation and Geoinformation on 28th September 2018 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/1810.00552" title="Abstract" id="1810.00552"> arXiv:1810.00552 </a> [<a href="/pdf/1810.00552" title="Download PDF" id="pdf-1810.00552" aria-labelledby="pdf-1810.00552">pdf</a>, <a href="/format/1810.00552" title="Other formats" id="oth-1810.00552" aria-labelledby="oth-1810.00552">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Power and Level Robustness of A Composite Hypothesis Testing under Independent Non-Homogeneous Data </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Ghosh,+A">Abhik Ghosh</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Basu,+A">Ayanendranath Basu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Pre-print, Under review </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Statistics & Probability Letters (2019) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/1810.00553" title="Abstract" id="1810.00553"> arXiv:1810.00553 </a> [<a href="/pdf/1810.00553" title="Download PDF" id="pdf-1810.00553" aria-labelledby="pdf-1810.00553">pdf</a>, <a href="/format/1810.00553" title="Other formats" id="oth-1810.00553" aria-labelledby="oth-1810.00553">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Adaptive and Accelerated Stochastic Gradient Descent </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Deng,+Q">Qi Deng</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cheng,+Y">Yi Cheng</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lan,+G">Guanghui Lan</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/1810.00555" title="Abstract" id="1810.00555"> arXiv:1810.00555 </a> [<a href="/pdf/1810.00555" title="Download PDF" id="pdf-1810.00555" aria-labelledby="pdf-1810.00555">pdf</a>, <a href="/format/1810.00555" title="Other formats" id="oth-1810.00555" aria-labelledby="oth-1810.00555">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Probabilistic Meta-Representations Of Neural Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Karaletsos,+T">Theofanis Karaletsos</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dayan,+P">Peter Dayan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ghahramani,+Z">Zoubin Ghahramani</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> presented at UAI 2018 Uncertainty In Deep Learning Workshop (UDL AUG. 2018) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/1810.00579" title="Abstract" id="1810.00579"> arXiv:1810.00579 </a> [<a href="/pdf/1810.00579" title="Download PDF" id="pdf-1810.00579" aria-labelledby="pdf-1810.00579">pdf</a>, <a href="/format/1810.00579" title="Other formats" id="oth-1810.00579" aria-labelledby="oth-1810.00579">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On valid descriptive inference from non-probability sample </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Zhang,+L">Li-Chun Zhang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/1810.00597" title="Abstract" id="1810.00597"> arXiv:1810.00597 </a> [<a href="/pdf/1810.00597" title="Download PDF" id="pdf-1810.00597" aria-labelledby="pdf-1810.00597">pdf</a>, <a href="/format/1810.00597" title="Other formats" id="oth-1810.00597" aria-labelledby="oth-1810.00597">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Taming VAEs </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rezende,+D+J">Danilo Jimenez Rezende</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Viola,+F">Fabio Viola</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/1810.00678" title="Abstract" id="1810.00678"> arXiv:1810.00678 </a> [<a href="/pdf/1810.00678" title="Download PDF" id="pdf-1810.00678" aria-labelledby="pdf-1810.00678">pdf</a>, <a href="/format/1810.00678" title="Other formats" id="oth-1810.00678" aria-labelledby="oth-1810.00678">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A nonparametric approach to assess undergraduate performance </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Pinheiro,+H+P">Hildete P. Pinheiro</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sen,+P+K">Pranab K. Sen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pinheiro,+A">Alu铆sio Pinheiro</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kiihl,+S+F">Samara F. Kiihl</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages, 6 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/1810.00680" title="Abstract" id="1810.00680"> arXiv:1810.00680 </a> [<a href="/pdf/1810.00680" title="Download PDF" id="pdf-1810.00680" aria-labelledby="pdf-1810.00680">pdf</a>, <a href="/format/1810.00680" title="Other formats" id="oth-1810.00680" aria-labelledby="oth-1810.00680">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Extremal properties of the multivariate extended skew-normal distribution </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Beranger,+B">Boris Beranger</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Padoan,+S+A">Simone A. Padoan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+Y">Yangfan Xu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sisson,+S+A">Scott A. Sisson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> arXiv admin note: substantial text overlap with <a href="https://arxiv.org/abs/1805.03316" data-arxiv-id="1805.03316" class="link-https">arXiv:1805.03316</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/1810.00709" title="Abstract" id="1810.00709"> arXiv:1810.00709 </a> [<a href="/pdf/1810.00709" title="Download PDF" id="pdf-1810.00709" aria-labelledby="pdf-1810.00709">pdf</a>, <a href="/format/1810.00709" title="Other formats" id="oth-1810.00709" aria-labelledby="oth-1810.00709">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> TOP: Time-to-Event Bayesian Optimal Phase II Trial Design for Cancer Immunotherapy </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lin,+R">Ruitao Lin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Coleman,+R+L">Robert L Coleman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yuan,+Y">Ying Yuan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages, 2 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/1810.00739" title="Abstract" id="1810.00739"> arXiv:1810.00739 </a> [<a href="/pdf/1810.00739" title="Download PDF" id="pdf-1810.00739" aria-labelledby="pdf-1810.00739">pdf</a>, <a href="/format/1810.00739" title="Other formats" id="oth-1810.00739" aria-labelledby="oth-1810.00739">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+C">Chang Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+Y">Yue Yang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bondell,+H">Howard Bondell</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Martin,+R">Ryan Martin</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 pages, 4 figures, 2 tables </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Statistica Sinica, volume 31, pages 2051--2072, 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/1810.00767" title="Abstract" id="1810.00767"> arXiv:1810.00767 </a> [<a href="/pdf/1810.00767" title="Download PDF" id="pdf-1810.00767" aria-labelledby="pdf-1810.00767">pdf</a>, <a href="/format/1810.00767" title="Other formats" id="oth-1810.00767" aria-labelledby="oth-1810.00767">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A nonparametric projection-based estimator for the probability of causation, with application to water sanitation in Kenya </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Cuellar,+M">Maria Cuellar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kennedy,+E+H">Edward H. Kennedy</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 24 pages, 6 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/1810.00787" title="Abstract" id="1810.00787"> arXiv:1810.00787 </a> [<a href="/pdf/1810.00787" title="Download PDF" id="pdf-1810.00787" aria-labelledby="pdf-1810.00787">pdf</a>, <a href="/format/1810.00787" title="Other formats" id="oth-1810.00787" aria-labelledby="oth-1810.00787">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Theory for BART </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rockova,+V">Veronika Rockova</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Saha,+E">Enakshi Saha</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/1810.00803" title="Abstract" id="1810.00803"> arXiv:1810.00803 </a> [<a href="/pdf/1810.00803" title="Download PDF" id="pdf-1810.00803" aria-labelledby="pdf-1810.00803">pdf</a>, <a href="/format/1810.00803" title="Other formats" id="oth-1810.00803" aria-labelledby="oth-1810.00803">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large Scale Clustering with Variational EM for Gaussian Mixture Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hirschberger,+F">Florian Hirschberger</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Forster,+D">Dennis Forster</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=L%C3%BCcke,+J">J枚rg L眉cke</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/1810.00828" title="Abstract" id="1810.00828"> arXiv:1810.00828 </a> [<a href="/pdf/1810.00828" title="Download PDF" id="pdf-1810.00828" aria-labelledby="pdf-1810.00828">pdf</a>, <a href="/format/1810.00828" title="Other formats" id="oth-1810.00828" aria-labelledby="oth-1810.00828">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Singularity, Misspecification, and the Convergence Rate of EM </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Dwivedi,+R">Raaz Dwivedi</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Ho,+N">Nhat Ho</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Khamaru,+K">Koulik Khamaru</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Jordan,+M+I">Michael I. Jordan</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Wainwright,+M+J">Martin J. Wainwright</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Yu,+B">Bin Yu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 63 pages, 12 figures. The first three authors contributed equally to this work. To appear in Annals of Statistics </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/1810.00832" title="Abstract" id="1810.00832"> arXiv:1810.00832 </a> [<a href="/pdf/1810.00832" title="Download PDF" id="pdf-1810.00832" aria-labelledby="pdf-1810.00832">pdf</a>, <a href="/format/1810.00832" title="Other formats" id="oth-1810.00832" aria-labelledby="oth-1810.00832">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Integrated Principal Components Analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tang,+T+M">Tiffany M. Tang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Allen,+G+I">Genevera I. Allen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/1810.00839" title="Abstract" id="1810.00839"> arXiv:1810.00839 </a> [<a href="/pdf/1810.00839" title="Download PDF" id="pdf-1810.00839" aria-labelledby="pdf-1810.00839">pdf</a>, <a href="/format/1810.00839" title="Other formats" id="oth-1810.00839" aria-labelledby="oth-1810.00839">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Network Modeling and Pathway Inference from Incomplete Data ("PathInf") </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+X">Xiang Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+Q">Qitian Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+X">Xing Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Guo,+N">Ning Guo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wu,+N">Nan Wu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Q">Quanzheng Li</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Xiang Li, Qitian Che and Xing Wang contribute equally to this work </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/1810.00908" title="Abstract" id="1810.00908"> arXiv:1810.00908 </a> [<a href="/pdf/1810.00908" title="Download PDF" id="pdf-1810.00908" aria-labelledby="pdf-1810.00908">pdf</a>, <a href="/format/1810.00908" title="Other formats" id="oth-1810.00908" aria-labelledby="oth-1810.00908">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Statistical Exploration of Duckworth-Lewis Method Using Bayesian Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bhattacharya,+I">Indrabati Bhattacharya</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ghosal,+R">Rahul Ghosal</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ghosh,+S">Sujit Ghosh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/1810.00919" title="Abstract" id="1810.00919"> arXiv:1810.00919 </a> [<a href="/pdf/1810.00919" title="Download PDF" id="pdf-1810.00919" aria-labelledby="pdf-1810.00919">pdf</a>, <a href="/format/1810.00919" title="Other formats" id="oth-1810.00919" aria-labelledby="oth-1810.00919">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robust multivariate and functional archetypal analysis with application to financial time series analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Moliner,+J">Jes煤s Moliner</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Epifanio,+I">Irene Epifanio</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Physica A: Statistical Mechanics and its Applications, 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Applications (stat.AP); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/1810.00969" title="Abstract" id="1810.00969"> arXiv:1810.00969 </a> [<a href="/pdf/1810.00969" title="Download PDF" id="pdf-1810.00969" aria-labelledby="pdf-1810.00969">pdf</a>, <a href="/format/1810.00969" title="Other formats" id="oth-1810.00969" aria-labelledby="oth-1810.00969">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the discovery of the seed in uniform attachment trees </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Devroye,+L">Luc Devroye</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Reddad,+T">Tommy Reddad</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Discrete Mathematics (cs.DM); Social and Information Networks (cs.SI); Probability (math.PR) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/1810.01005" title="Abstract" id="1810.01005"> arXiv:1810.01005 </a> [<a href="/pdf/1810.01005" title="Download PDF" id="pdf-1810.01005" aria-labelledby="pdf-1810.01005">pdf</a>, <a href="/format/1810.01005" title="Other formats" id="oth-1810.01005" aria-labelledby="oth-1810.01005">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> plsRglm: Partial least squares linear and generalized linear regression for processing incomplete datasets by cross-validation and bootstrap techniques with R </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bertrand,+F">F. Bertrand</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Maumy-Bertrand,+M">M. Maumy-Bertrand</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages, 8 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/1810.01061" title="Abstract" id="1810.01061"> arXiv:1810.01061 </a> [<a href="/pdf/1810.01061" title="Download PDF" id="pdf-1810.01061" aria-labelledby="pdf-1810.01061">pdf</a>, <a href="/format/1810.01061" title="Other formats" id="oth-1810.01061" aria-labelledby="oth-1810.01061">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Feature Selection Approach with Missing Values Conducted for Statistical Learning: A Case Study of Entrepreneurship Survival Dataset </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Nascimento,+D">Diego Nascimento</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ara,+A">Anderson Ara</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Neto,+F+L">Francisco Louzada Neto</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/1810.01072" title="Abstract" id="1810.01072"> arXiv:1810.01072 </a> [<a href="/pdf/1810.01072" title="Download PDF" id="pdf-1810.01072" aria-labelledby="pdf-1810.01072">pdf</a>, <a href="/format/1810.01072" title="Other formats" id="oth-1810.01072" aria-labelledby="oth-1810.01072">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A flexible sequential Monte Carlo algorithm for parametric constrained regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ng,+K">Kenyon Ng</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Turlach,+B+A">Berwin A. Turlach</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Murray,+K">Kevin Murray</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Typo corrections. Code available on <a href="https://github.com/weiyaw/blackbox" 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> Computational Statistics & Data Analysis 138 (2019) 13-26 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Computation (stat.CO) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/1810.01090" title="Abstract" id="1810.01090"> arXiv:1810.01090 </a> [<a href="/pdf/1810.01090" title="Download PDF" id="pdf-1810.01090" aria-labelledby="pdf-1810.01090">pdf</a>, <a href="/format/1810.01090" title="Other formats" id="oth-1810.01090" aria-labelledby="oth-1810.01090">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Statistical learning with Lipschitz and convex loss functions </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Chinot,+G">Geoffrey Chinot</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Guillaume,+L">Lecu茅 Guillaume</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Matthieu,+L">Lerasle Matthieu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/1810.01116" title="Abstract" id="1810.01116"> arXiv:1810.01116 </a> [<a href="/pdf/1810.01116" title="Download PDF" id="pdf-1810.01116" aria-labelledby="pdf-1810.01116">pdf</a>, <a href="/format/1810.01116" title="Other formats" id="oth-1810.01116" aria-labelledby="oth-1810.01116">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Inverse Gaussian quadrature and finite normal-mixture approximation of the generalized hyperbolic distribution </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Choi,+J">Jaehyuk Choi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Du,+Y">Yeda Du</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+Q">Qingshuo Song</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Computational and Applied Mathematics, 388:113302, 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Computational Finance (q-fin.CP); Pricing of Securities (q-fin.PR) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/1810.01147" title="Abstract" id="1810.01147"> arXiv:1810.01147 </a> [<a href="/pdf/1810.01147" title="Download PDF" id="pdf-1810.01147" aria-labelledby="pdf-1810.01147">pdf</a>, <a href="/format/1810.01147" title="Other formats" id="oth-1810.01147" aria-labelledby="oth-1810.01147">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On characterizations of the covariance matrix </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Virta,+J">Joni Virta</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 11 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/1810.01174" title="Abstract" id="1810.01174"> arXiv:1810.01174 </a> [<a href="/pdf/1810.01174" title="Download PDF" id="pdf-1810.01174" aria-labelledby="pdf-1810.01174">pdf</a>, <a href="/format/1810.01174" title="Other formats" id="oth-1810.01174" aria-labelledby="oth-1810.01174">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Identification of oscillatory brain networks with Hidden Gaussian Graphical Spectral models of EEG/MEG </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Paz-Linares,+D">Deirel Paz-Linares</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gonzalez-Moreira,+E">Eduardo Gonzalez-Moreira</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Areces-Gonzalez,+A">Ariosky Areces-Gonzalez</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Ying Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+M">Min Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Martinez-Montes,+E">Eduardo Martinez-Montes</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bosch-Bayard,+J">Jorge Bosch-Bayard</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bringas-Vega,+M+L">Maria L. Bringas-Vega</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Valdes-Sosa,+M+J">Mitchel J. Valdes-Sosa</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Valdes-Sosa,+P+A">Pedro A. Valdes-Sosa</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Neurons and Cognition (q-bio.NC) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/1810.01195" title="Abstract" id="1810.01195"> arXiv:1810.01195 </a> [<a href="/pdf/1810.01195" title="Download PDF" id="pdf-1810.01195" aria-labelledby="pdf-1810.01195">pdf</a>, <a href="/format/1810.01195" title="Other formats" id="oth-1810.01195" aria-labelledby="oth-1810.01195">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> High-dimensional functional time series forecasting: An application to age-specific mortality rates </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gao,+Y">Yuan Gao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shang,+H+L">Han Lin Shang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+Y">Yanrong Yang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages, 2 figures, To appear in Journal of Multivariate Analysis </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/1810.01203" title="Abstract" id="1810.01203"> arXiv:1810.01203 </a> [<a href="/pdf/1810.01203" title="Download PDF" id="pdf-1810.01203" aria-labelledby="pdf-1810.01203">pdf</a>, <a href="/format/1810.01203" title="Other formats" id="oth-1810.01203" aria-labelledby="oth-1810.01203">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Consistent Maximum Likelihood Estimation Using Subsets with Applications to Multivariate Mixed Models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Ekvall,+K+O">Karl Oskar Ekvall</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Jones,+G+L">Galin L. Jones</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/1810.01294" title="Abstract" id="1810.01294"> arXiv:1810.01294 </a> [<a href="/pdf/1810.01294" title="Download PDF" id="pdf-1810.01294" aria-labelledby="pdf-1810.01294">pdf</a>, <a href="/format/1810.01294" title="Other formats" id="oth-1810.01294" aria-labelledby="oth-1810.01294">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Causal inference under over-simplified longitudinal causal models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Etievant,+L">Lola Etievant</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Viallon,+V">Vivian Viallon</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1810.01296" title="Abstract" id="1810.01296"> arXiv:1810.01296 </a> [<a href="/pdf/1810.01296" title="Download PDF" id="pdf-1810.01296" aria-labelledby="pdf-1810.01296">pdf</a>, <a href="/format/1810.01296" title="Other formats" id="oth-1810.01296" aria-labelledby="oth-1810.01296">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bias Reduced Peaks over Threshold Tail Estimation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Beirlant,+J">Jan Beirlant</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Maribe,+G">Gaonyalelwe Maribe</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Naveau,+P">Philippe Naveau</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Verster,+A">Andrehette Verster</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/1810.01300" title="Abstract" id="1810.01300"> arXiv:1810.01300 </a> [<a href="/pdf/1810.01300" title="Download PDF" id="pdf-1810.01300" aria-labelledby="pdf-1810.01300">pdf</a>, <a href="/format/1810.01300" title="Other formats" id="oth-1810.01300" aria-labelledby="oth-1810.01300">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sampling-based Estimation of In-degree Distribution with Applications to Directed Complex Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Antunes,+N">Nelson Antunes</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bhamidi,+S">Shankar Bhamidi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Guo,+T">Tianjian Guo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pipiras,+V">Vladas Pipiras</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+B">Bang Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 30 pages , 6 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Social and Information Networks (cs.SI); Physics and Society (physics.soc-ph) </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/1810.01323" title="Abstract" id="1810.01323"> arXiv:1810.01323 </a> [<a href="/pdf/1810.01323" title="Download PDF" id="pdf-1810.01323" aria-labelledby="pdf-1810.01323">pdf</a>, <a href="/format/1810.01323" title="Other formats" id="oth-1810.01323" aria-labelledby="oth-1810.01323">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Moderate-Dimensional Inferences on Quadratic Functionals in Ordinary Least Squares </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Guo,+X">Xiao Guo</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Cheng,+G">Guang Cheng</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appear in JASA-T&M </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> </dl> <div class='paging'>Total of 1364 entries : <span>1-50</span> <a href=/list/stat/2018-10?skip=50&show=50>51-100</a> <a href=/list/stat/2018-10?skip=100&show=50>101-150</a> <a href=/list/stat/2018-10?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2018-10?skip=1350&show=50>1351-1364</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2018-10?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2018-10?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2018-10?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; 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