Statistics Jan 2019

<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Jan 2019</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/2019-01?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2019-01?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2019-01?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1901.00052" title="Abstract" id="1901.00052"> arXiv:1901.00052 </a> [<a href="/pdf/1901.00052" title="Download PDF" id="pdf-1901.00052" aria-labelledby="pdf-1901.00052">pdf</a>, <a href="/format/1901.00052" title="Other formats" id="oth-1901.00052" aria-labelledby="oth-1901.00052">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Clustering and Trend Analysis of Global Extreme Droughts from 1900 to 2014 </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Najafi,+E">Ehsan Najafi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Khanbilvardi,+R">Reza Khanbilvardi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 1 table, 13 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Atmospheric and Oceanic Physics (physics.ao-ph) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/1901.00068" title="Abstract" id="1901.00068"> arXiv:1901.00068 </a> [<a href="/pdf/1901.00068" title="Download PDF" id="pdf-1901.00068" aria-labelledby="pdf-1901.00068">pdf</a>, <a href="/format/1901.00068" title="Other formats" id="oth-1901.00068" aria-labelledby="oth-1901.00068">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian Spatial Model for Imaging Genetics </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+Y">Yin Song</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ge,+S">Shufei Ge</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cao,+J">Jiguo Cao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+L">Liangliang Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nathoo,+F+S">Farouk S. Nathoo</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/1901.00089" title="Abstract" id="1901.00089"> arXiv:1901.00089 </a> [<a href="/pdf/1901.00089" title="Download PDF" id="pdf-1901.00089" aria-labelledby="pdf-1901.00089">pdf</a>, <a href="/format/1901.00089" title="Other formats" id="oth-1901.00089" aria-labelledby="oth-1901.00089">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Approximation of the Cell Under Test in Sliding Window Detection Processes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Weinberg,+G+V">Graham V. Weinberg</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Progress In Electromagnetics Research Letters, Vol. 84, 75-81, 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/1901.00103" title="Abstract" id="1901.00103"> arXiv:1901.00103 </a> [<a href="/pdf/1901.00103" title="Download PDF" id="pdf-1901.00103" aria-labelledby="pdf-1901.00103">pdf</a>, <a href="/format/1901.00103" title="Other formats" id="oth-1901.00103" aria-labelledby="oth-1901.00103">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Statistical Analysis Of NYC Buildings And Wind Damages </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Azimi,+E">Elham Azimi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Griffis,+B">Bud Griffis</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='item5'>[5]</a> <a href ="/abs/1901.00139" title="Abstract" id="1901.00139"> arXiv:1901.00139 </a> [<a href="/pdf/1901.00139" title="Download PDF" id="pdf-1901.00139" aria-labelledby="pdf-1901.00139">pdf</a>, <a href="/format/1901.00139" title="Other formats" id="oth-1901.00139" aria-labelledby="oth-1901.00139">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Monte Carlo Fusion </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Dai,+H">Hongsheng Dai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pollock,+M">Murray Pollock</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Roberts,+G">Gareth Roberts</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> J. Appl. Probab. 56 (2019) 174-191 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/1901.00140" title="Abstract" id="1901.00140"> arXiv:1901.00140 </a> [<a href="/pdf/1901.00140" title="Download PDF" id="pdf-1901.00140" aria-labelledby="pdf-1901.00140">pdf</a>, <a href="/format/1901.00140" title="Other formats" id="oth-1901.00140" aria-labelledby="oth-1901.00140">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Adaptive Quantile Low-Rank Matrix Factorization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+S">Shuang Xu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+C">Chun-Xia Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+J">Jiangshe Zhang</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Pattern Recognition, Volume 103, July 2020, 107310 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/1901.00150" title="Abstract" id="1901.00150"> arXiv:1901.00150 </a> [<a href="/pdf/1901.00150" title="Download PDF" id="pdf-1901.00150" aria-labelledby="pdf-1901.00150">pdf</a>, <a href="/format/1901.00150" title="Other formats" id="oth-1901.00150" aria-labelledby="oth-1901.00150">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Accelerated MM Algorithms for Ranking Scores Inference from Comparison Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Vojnovic,+M">Milan Vojnovic</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yun,+S">Seyoung Yun</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhou,+K">Kaifang Zhou</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/1901.00180" title="Abstract" id="1901.00180"> arXiv:1901.00180 </a> [<a href="/pdf/1901.00180" title="Download PDF" id="pdf-1901.00180" aria-labelledby="pdf-1901.00180">pdf</a>, <a href="/format/1901.00180" title="Other formats" id="oth-1901.00180" aria-labelledby="oth-1901.00180">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Depth for curve data and applications </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=de+Micheaux,+P+L">Pierre Lafaye de Micheaux</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mozharovskyi,+P">Pavlo Mozharovskyi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vimond,+M">Myriam Vimond</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/1901.00213" title="Abstract" id="1901.00213"> arXiv:1901.00213 </a> [<a href="/pdf/1901.00213" title="Download PDF" id="pdf-1901.00213" aria-labelledby="pdf-1901.00213">pdf</a>, <a href="/format/1901.00213" title="Other formats" id="oth-1901.00213" aria-labelledby="oth-1901.00213">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A weighted random survival forest </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Utkin,+L+V">Lev V. Utkin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Konstantinov,+A+V">Andrei V. Konstantinov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chukanov,+V+S">Viacheslav S. Chukanov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kots,+M+V">Mikhail V. Kots</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ryabinin,+M+A">Mikhail A. Ryabinin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meldo,+A+A">Anna A. Meldo</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='item10'>[10]</a> <a href ="/abs/1901.00226" title="Abstract" id="1901.00226"> arXiv:1901.00226 </a> [<a href="/pdf/1901.00226" title="Download PDF" id="pdf-1901.00226" aria-labelledby="pdf-1901.00226">pdf</a>, <a href="/format/1901.00226" title="Other formats" id="oth-1901.00226" aria-labelledby="oth-1901.00226">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Statistical inference for Bures-Wasserstein barycenters </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kroshnin,+A">Alexey Kroshnin</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Spokoiny,+V">Vladimir Spokoiny</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Suvorikova,+A">Alexandra Suvorikova</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 37 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/1901.00250" title="Abstract" id="1901.00250"> arXiv:1901.00250 </a> [<a href="/pdf/1901.00250" title="Download PDF" id="pdf-1901.00250" aria-labelledby="pdf-1901.00250">pdf</a>, <a href="/format/1901.00250" title="Other formats" id="oth-1901.00250" aria-labelledby="oth-1901.00250">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Extension of the Geometric Mean Constant False Alarm Rate Detector to Multiple Pulses </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Weinberg,+G+V">Graham V. Weinberg</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/1901.00251" title="Abstract" id="1901.00251"> arXiv:1901.00251 </a> [<a href="/pdf/1901.00251" title="Download PDF" id="pdf-1901.00251" aria-labelledby="pdf-1901.00251">pdf</a>, <a href="/format/1901.00251" title="Other formats" id="oth-1901.00251" aria-labelledby="oth-1901.00251">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Automatic Interaction Detection Hybrid Model for Bankcard Response Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yan Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ni,+X+S">Xuelei Sherry Ni</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Stone,+B">Brian Stone</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> The 2018 5th International Conference on Systems and Informatics (ICSAI2018) </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='item13'>[13]</a> <a href ="/abs/1901.00304" title="Abstract" id="1901.00304"> arXiv:1901.00304 </a> [<a href="/pdf/1901.00304" title="Download PDF" id="pdf-1901.00304" aria-labelledby="pdf-1901.00304">pdf</a>, <a href="/format/1901.00304" title="Other formats" id="oth-1901.00304" aria-labelledby="oth-1901.00304">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Normal Approximation and Confidence Region of Singular Subspaces </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Xia,+D">Dong Xia</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Information Theory (cs.IT); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/1901.00331" title="Abstract" id="1901.00331"> arXiv:1901.00331 </a> [<a href="/pdf/1901.00331" title="Download PDF" id="pdf-1901.00331" aria-labelledby="pdf-1901.00331">pdf</a>, <a href="/format/1901.00331" title="Other formats" id="oth-1901.00331" aria-labelledby="oth-1901.00331">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Kernel Density Estimation Bias under Minimal Assumptions </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Skorski,+M">Maciej Skorski</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Machine Learning (cs.LG); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/1901.00336" title="Abstract" id="1901.00336"> arXiv:1901.00336 </a> [<a href="/pdf/1901.00336" title="Download PDF" id="pdf-1901.00336" aria-labelledby="pdf-1901.00336">pdf</a>, <a href="/format/1901.00336" title="Other formats" id="oth-1901.00336" aria-labelledby="oth-1901.00336">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Modelling the clustering of extreme events for short-term risk assessment </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Towe,+R">Ross Towe</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tawn,+J">Jonathan Tawn</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Eastoe,+E">Emma Eastoe</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lamb,+R">Rob Lamb</a></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='item16'>[16]</a> <a href ="/abs/1901.00359" title="Abstract" id="1901.00359"> arXiv:1901.00359 </a> [<a href="/pdf/1901.00359" title="Download PDF" id="pdf-1901.00359" aria-labelledby="pdf-1901.00359">pdf</a>, <a href="/format/1901.00359" title="Other formats" id="oth-1901.00359" aria-labelledby="oth-1901.00359">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Inference for spherical location under high concentration </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Paindaveine,+D">Davy Paindaveine</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Verdebout,+T">Thomas Verdebout</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 51 pages, 5 figures </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='item17'>[17]</a> <a href ="/abs/1901.00402" title="Abstract" id="1901.00402"> arXiv:1901.00402 </a> [<a href="/pdf/1901.00402" title="Download PDF" id="pdf-1901.00402" aria-labelledby="pdf-1901.00402">pdf</a>, <a href="/format/1901.00402" title="Other formats" id="oth-1901.00402" aria-labelledby="oth-1901.00402">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Anomaly Detection in Networks with Application to Financial Transaction Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Elliott,+A">Andrew Elliott</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cucuringu,+M">Mihai Cucuringu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Luaces,+M+M">Milton Martinez Luaces</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Reidy,+P">Paul Reidy</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Reinert,+G">Gesine Reinert</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Social and Information Networks (cs.SI); Physics and Society (physics.soc-ph) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/1901.00403" title="Abstract" id="1901.00403"> arXiv:1901.00403 </a> [<a href="/pdf/1901.00403" title="Download PDF" id="pdf-1901.00403" aria-labelledby="pdf-1901.00403">pdf</a>, <a href="/format/1901.00403" title="Other formats" id="oth-1901.00403" aria-labelledby="oth-1901.00403">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Can You Trust This Prediction? Auditing Pointwise Reliability After Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Schulam,+P">Peter Schulam</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Saria,+S">Suchi Saria</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appear in the proceedings of Artificial Intelligence and Statistics (AISTATS) 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/1901.00409" title="Abstract" id="1901.00409"> arXiv:1901.00409 </a> [<a href="/pdf/1901.00409" title="Download PDF" id="pdf-1901.00409" aria-labelledby="pdf-1901.00409">pdf</a>, <a href="/format/1901.00409" title="Other formats" id="oth-1901.00409" aria-labelledby="oth-1901.00409">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural Clustering Processes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Pakman,+A">Ari Pakman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yueqi Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mitelut,+C">Catalin Mitelut</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lee,+J">JinHyung Lee</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Paninski,+L">Liam Paninski</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Published in Proceedings of the 37th International Conference on Machine Learning, Vienna, Austria, PMLR 119, 2020 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/1901.00433" title="Abstract" id="1901.00433"> arXiv:1901.00433 </a> [<a href="/pdf/1901.00433" title="Download PDF" id="pdf-1901.00433" aria-labelledby="pdf-1901.00433">pdf</a>, <a href="/format/1901.00433" title="Other formats" id="oth-1901.00433" aria-labelledby="oth-1901.00433">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Forr%C3%A9,+P">Patrick Forr茅</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mooij,+J+M">Joris M. Mooij</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for publication in Conference on Uncertainty in Artificial Intelligence 2019 (UAI-2019) </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of the 35th Annual Conference on Uncertainty in Artificial Intelligence, 2019 </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); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/1901.00456" title="Abstract" id="1901.00456"> arXiv:1901.00456 </a> [<a href="/pdf/1901.00456" title="Download PDF" id="pdf-1901.00456" aria-labelledby="pdf-1901.00456">pdf</a>, <a href="/format/1901.00456" title="Other formats" id="oth-1901.00456" aria-labelledby="oth-1901.00456">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Cost-sensitive Selection of Variables by Ensemble of Model Sequences </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yan,+D">Donghui Yan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Qin,+Z">Zhiwei Qin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gu,+S">Songxiang Gu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+H">Haiping Xu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shao,+M">Ming Shao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 13 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Machine Learning (cs.LG); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/1901.00533" title="Abstract" id="1901.00533"> arXiv:1901.00533 </a> [<a href="/pdf/1901.00533" title="Download PDF" id="pdf-1901.00533" aria-labelledby="pdf-1901.00533">pdf</a>, <a href="/format/1901.00533" title="Other formats" id="oth-1901.00533" aria-labelledby="oth-1901.00533">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Simple Algorithm for Scalable Monte Carlo Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Borisenko,+A">Alexander Borisenko</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Byshkin,+M">Maksym Byshkin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lomi,+A">Alessandro Lomi</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages + supplementary information </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Mathematical Physics (math-ph); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/1901.00615" title="Abstract" id="1901.00615"> arXiv:1901.00615 </a> [<a href="/pdf/1901.00615" title="Download PDF" id="pdf-1901.00615" aria-labelledby="pdf-1901.00615">pdf</a>, <a href="/format/1901.00615" title="Other formats" id="oth-1901.00615" aria-labelledby="oth-1901.00615">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Structure learning via unstructured kernel-based M-regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=He,+X">Xin He</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ge,+Y">Yeheng Ge</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Feng,+X">Xingdong Feng</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='item24'>[24]</a> <a href ="/abs/1901.00630" title="Abstract" id="1901.00630"> arXiv:1901.00630 </a> [<a href="/pdf/1901.00630" title="Download PDF" id="pdf-1901.00630" aria-labelledby="pdf-1901.00630">pdf</a>, <a href="/format/1901.00630" title="Other formats" id="oth-1901.00630" aria-labelledby="oth-1901.00630">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Projecting "better than randomly": How to reduce the dimensionality of very large datasets in a way that outperforms random projections </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wojnowicz,+M">Michael Wojnowicz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+D">Di Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chisholm,+G">Glenn Chisholm</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+X">Xuan Zhao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wolff,+M">Matt Wolff</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Originally published in IEEE DSAA in 2016; this post-print fixes a rendering error of the += operator in Algorithm 3 </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> 2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (DSAA) (pp. 184-193). IEEE </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/1901.00663" title="Abstract" id="1901.00663"> arXiv:1901.00663 </a> [<a href="/pdf/1901.00663" title="Download PDF" id="pdf-1901.00663" aria-labelledby="pdf-1901.00663">pdf</a>, <a href="/format/1901.00663" title="Other formats" id="oth-1901.00663" aria-labelledby="oth-1901.00663">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient augmentation and relaxation learning for individualized treatment rules using observational data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+Y">Ying-Qi Zhao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Laber,+E+B">Eric B. Laber</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ning,+Y">Yang Ning</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Saha,+S">Sumona Saha</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sands,+B">Bruce Sands</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='item26'>[26]</a> <a href ="/abs/1901.00699" title="Abstract" id="1901.00699"> arXiv:1901.00699 </a> [<a href="/pdf/1901.00699" title="Download PDF" id="pdf-1901.00699" aria-labelledby="pdf-1901.00699">pdf</a>, <a href="/format/1901.00699" title="Other formats" id="oth-1901.00699" aria-labelledby="oth-1901.00699">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Data breaches in the catastrophe framework & beyond </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wheatley,+S">Spencer Wheatley</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hofmann,+A">Annette Hofmann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sornette,+D">Didier Sornette</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Previous version presented at Symposium on Insurance and Emerging Risks, St. John's University, March 10th, 2018 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Computers and Society (cs.CY) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/1901.00772" title="Abstract" id="1901.00772"> arXiv:1901.00772 </a> [<a href="/pdf/1901.00772" title="Download PDF" id="pdf-1901.00772" aria-labelledby="pdf-1901.00772">pdf</a>, <a href="/format/1901.00772" title="Other formats" id="oth-1901.00772" aria-labelledby="oth-1901.00772">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Which practical interventions does the do-operator refer to in causal inference? Illustration on the example of obesity and cancer </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='item28'>[28]</a> <a href ="/abs/1901.00781" title="Abstract" id="1901.00781"> arXiv:1901.00781 </a> [<a href="/pdf/1901.00781" title="Download PDF" id="pdf-1901.00781" aria-labelledby="pdf-1901.00781">pdf</a>, <a href="/format/1901.00781" title="Other formats" id="oth-1901.00781" aria-labelledby="oth-1901.00781">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning a Generator Model from Terminal Bus Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Stulov,+N">Nikolay Stulov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sobajic,+D+J">Dejan J Sobajic</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Maximov,+Y">Yury Maximov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Deka,+D">Deepjyoti Deka</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chertkov,+M">Michael Chertkov</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 6 pages, 9 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Electric Power Systems Research Journal, 2020 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/1901.00833" title="Abstract" id="1901.00833"> arXiv:1901.00833 </a> [<a href="/pdf/1901.00833" title="Download PDF" id="pdf-1901.00833" aria-labelledby="pdf-1901.00833">pdf</a>, <a href="/format/1901.00833" title="Other formats" id="oth-1901.00833" aria-labelledby="oth-1901.00833">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Energy distance and kernel mean embedding for two sample survival test </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Matabuena,+M">Marcos Matabuena</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/1901.00880" title="Abstract" id="1901.00880"> arXiv:1901.00880 </a> [<a href="/pdf/1901.00880" title="Download PDF" id="pdf-1901.00880" aria-labelledby="pdf-1901.00880">pdf</a>, <a href="/format/1901.00880" title="Other formats" id="oth-1901.00880" aria-labelledby="oth-1901.00880">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Minimax $L_2$-Separation Rate in Testing the Sobolev-Type Regularity of a function </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Gutzeit,+M">Maurilio Gutzeit</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='item31'>[31]</a> <a href ="/abs/1901.00883" title="Abstract" id="1901.00883"> arXiv:1901.00883 </a> [<a href="/pdf/1901.00883" title="Download PDF" id="pdf-1901.00883" aria-labelledby="pdf-1901.00883">pdf</a>, <a href="/format/1901.00883" title="Other formats" id="oth-1901.00883" aria-labelledby="oth-1901.00883">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Enhanced Welding Operator Quality Performance Measurement: Work Experience-Integrated Bayesian Prior Determination </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Y">Yitong Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ji,+W">Wenying Ji</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=AbouRizk,+S+M">Simaan M. AbouRizk</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 5 figures, 2 tables, i3CE 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/1901.00886" title="Abstract" id="1901.00886"> arXiv:1901.00886 </a> [<a href="/pdf/1901.00886" title="Download PDF" id="pdf-1901.00886" aria-labelledby="pdf-1901.00886">pdf</a>, <a href="/format/1901.00886" title="Other formats" id="oth-1901.00886" aria-labelledby="oth-1901.00886">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonparametric graphical model for counts </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Roy,+A">Arkaprava Roy</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dunson,+D+B">David B Dunson</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='item33'>[33]</a> <a href ="/abs/1901.00908" title="Abstract" id="1901.00908"> arXiv:1901.00908 </a> [<a href="/pdf/1901.00908" title="Download PDF" id="pdf-1901.00908" aria-labelledby="pdf-1901.00908">pdf</a>, <a href="/format/1901.00908" title="Other formats" id="oth-1901.00908" aria-labelledby="oth-1901.00908">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Longitudinal Causal Inference in the Analysis of the Public Health Impact of Pollutant Emissions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kim,+C">Chanmin Kim</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zigler,+C+M">Corwin M Zigler</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Daniels,+M+J">Michael J Daniels</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Choirat,+C">Christine Choirat</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Roy,+J+A">Jason A Roy</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/1901.00914" title="Abstract" id="1901.00914"> arXiv:1901.00914 </a> [<a href="/pdf/1901.00914" title="Download PDF" id="pdf-1901.00914" aria-labelledby="pdf-1901.00914">pdf</a>, <a href="/format/1901.00914" title="Other formats" id="oth-1901.00914" aria-labelledby="oth-1901.00914">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Element-wise estimation error of a total variation regularized estimator for change point detection </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Zhang,+T">Teng 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='item35'>[35]</a> <a href ="/abs/1901.01000" title="Abstract" id="1901.01000"> arXiv:1901.01000 </a> [<a href="/pdf/1901.01000" title="Download PDF" id="pdf-1901.01000" aria-labelledby="pdf-1901.01000">pdf</a>, <a href="/format/1901.01000" title="Other formats" id="oth-1901.01000" aria-labelledby="oth-1901.01000">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fast Multi-Class Probabilistic Classifier by Sparse Non-parametric Density Estimation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+W+N">Wan-Ping Nicole Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chang,+Y+I">Yuan-chin Ivan Chang</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='item36'>[36]</a> <a href ="/abs/1901.01026" title="Abstract" id="1901.01026"> arXiv:1901.01026 </a> [<a href="/pdf/1901.01026" title="Download PDF" id="pdf-1901.01026" aria-labelledby="pdf-1901.01026">pdf</a>, <a href="/format/1901.01026" title="Other formats" id="oth-1901.01026" aria-labelledby="oth-1901.01026">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On central limit theorems for power variations of the solution to the stochastic heat equation </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Bibinger,+M">Markus Bibinger</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Trabs,+M">Mathias Trabs</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">Statistics Theory (math.ST)</span>; Probability (math.PR) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/1901.01030" title="Abstract" id="1901.01030"> arXiv:1901.01030 </a> [<a href="/pdf/1901.01030" title="Download PDF" id="pdf-1901.01030" aria-labelledby="pdf-1901.01030">pdf</a>, <a href="/format/1901.01030" title="Other formats" id="oth-1901.01030" aria-labelledby="oth-1901.01030">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multi-Product Dynamic Pricing in High-Dimensions with Heterogeneous Price Sensitivity </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Javanmard,+A">Adel Javanmard</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nazerzadeh,+H">Hamid Nazerzadeh</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shao,+S">Simeng Shao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 24 pages, 1 figure </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Computer Science and Game Theory (cs.GT); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/1901.01077" title="Abstract" id="1901.01077"> arXiv:1901.01077 </a> [<a href="/pdf/1901.01077" title="Download PDF" id="pdf-1901.01077" aria-labelledby="pdf-1901.01077">pdf</a>, <a href="/format/1901.01077" title="Other formats" id="oth-1901.01077" aria-labelledby="oth-1901.01077">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Testing for strict stationarity in a random coefficient autoregressive model </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Trapani,+L">Lorenzo Trapani</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='item39'>[39]</a> <a href ="/abs/1901.01163" title="Abstract" id="1901.01163"> arXiv:1901.01163 </a> [<a href="/pdf/1901.01163" title="Download PDF" id="pdf-1901.01163" aria-labelledby="pdf-1901.01163">pdf</a>, <a href="/format/1901.01163" title="Other formats" id="oth-1901.01163" aria-labelledby="oth-1901.01163">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Approximating high-dimensional infinite-order $U$-statistics: statistical and computational guarantees </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Song,+Y">Yanglei Song</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Chen,+X">Xiaohui Chen</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Kato,+K">Kengo Kato</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Electronic Journal of Statistics 2019, Vol. 13, No. 2, 4794-4848 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/1901.01230" title="Abstract" id="1901.01230"> arXiv:1901.01230 </a> [<a href="/pdf/1901.01230" title="Download PDF" id="pdf-1901.01230" aria-labelledby="pdf-1901.01230">pdf</a>, <a href="/format/1901.01230" title="Other formats" id="oth-1901.01230" aria-labelledby="oth-1901.01230">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Permutation Weighting </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Arbour,+D">David Arbour</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dimmery,+D">Drew Dimmery</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sondhi,+A">Arjun Sondhi</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='item41'>[41]</a> <a href ="/abs/1901.01303" title="Abstract" id="1901.01303"> arXiv:1901.01303 </a> [<a href="/pdf/1901.01303" title="Download PDF" id="pdf-1901.01303" aria-labelledby="pdf-1901.01303">pdf</a>, <a href="/format/1901.01303" title="Other formats" id="oth-1901.01303" aria-labelledby="oth-1901.01303">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The i3+3 Design for Phase I Clinical Trials </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+M">Meizi Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+S">Sue-Jane Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ji,+Y">Yuan Ji</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 39 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/1901.01308" title="Abstract" id="1901.01308"> arXiv:1901.01308 </a> [<a href="/pdf/1901.01308" title="Download PDF" id="pdf-1901.01308" aria-labelledby="pdf-1901.01308">pdf</a>, <a href="/format/1901.01308" title="Other formats" id="oth-1901.01308" aria-labelledby="oth-1901.01308">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Integrating Phase 2 into Phase 3 based on an Intermediate Endpoint While Accounting for a Cure Proportion -- with an Application to the Design of a Clinical Trial in Acute Myeloid Leukemia </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rufibach,+K">Kaspar Rufibach</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Heinzmann,+D">Dominik Heinzmann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Monnet,+A">Annabelle Monnet</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 23 pages, 3 figures, 3 tables. All code is available on github: <a href="https://github.com/numbersman77/integratePhase2.git" 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> Pharm. Stat., 2020, 19, 44-58 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/1901.01330" title="Abstract" id="1901.01330"> arXiv:1901.01330 </a> [<a href="/pdf/1901.01330" title="Download PDF" id="pdf-1901.01330" aria-labelledby="pdf-1901.01330">pdf</a>, <a href="/format/1901.01330" title="Other formats" id="oth-1901.01330" aria-labelledby="oth-1901.01330">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Spatiotemporal Calibration of Atmospheric Nitrogen Dioxide Concentration Estimates From an Air Quality Model for Connecticut </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gilani,+O">Owais Gilani</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=McKay,+L+A">Lisa A. McKay</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gregoire,+T+G">Timothy G. Gregoire</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Guan,+Y">Yongtao Guan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Leaderer,+B+P">Brian P. Leaderer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Holford,+T+R">Theodore R. Holford</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 23 pages, 8 figures, supplementary material </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/1901.01334" title="Abstract" id="1901.01334"> arXiv:1901.01334 </a> [<a href="/pdf/1901.01334" title="Download PDF" id="pdf-1901.01334" aria-labelledby="pdf-1901.01334">pdf</a>, <a href="/format/1901.01334" title="Other formats" id="oth-1901.01334" aria-labelledby="oth-1901.01334">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Adaptive Weighted Deep Forest Classifier </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Utkin,+L+V">Lev V. Utkin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Konstantinov,+A+V">Andrei V. Konstantinov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chukanov,+V+S">Viacheslav S. Chukanov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kots,+M+V">Mikhail V. Kots</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meldo,+A+A">Anna A. Meldo</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='item45'>[45]</a> <a href ="/abs/1901.01336" title="Abstract" id="1901.01336"> arXiv:1901.01336 </a> [<a href="/pdf/1901.01336" title="Download PDF" id="pdf-1901.01336" aria-labelledby="pdf-1901.01336">pdf</a>, <a href="/format/1901.01336" title="Other formats" id="oth-1901.01336" aria-labelledby="oth-1901.01336">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Projective Decomposition and Matrix Equivalence up to Scale </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Robinson,+M">Max Robinson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Other Statistics (stat.OT)</span>; Computer Vision and Pattern Recognition (cs.CV); Metric Geometry (math.MG) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/1901.01338" title="Abstract" id="1901.01338"> arXiv:1901.01338 </a> [<a href="/pdf/1901.01338" title="Download PDF" id="pdf-1901.01338" aria-labelledby="pdf-1901.01338">pdf</a>, <a href="/format/1901.01338" title="Other formats" id="oth-1901.01338" aria-labelledby="oth-1901.01338">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Distributions of Human Exposure to Ozone During Commuting Hours in Connecticut using the Cellular Device Network </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gilani,+O">Owais Gilani</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Urbanek,+S">Simon Urbanek</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kane,+M+J">Michael J. Kane</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='item47'>[47]</a> <a href ="/abs/1901.01375" title="Abstract" id="1901.01375"> arXiv:1901.01375 </a> [<a href="/pdf/1901.01375" title="Download PDF" id="pdf-1901.01375" aria-labelledby="pdf-1901.01375">pdf</a>, <a href="/format/1901.01375" title="Other formats" id="oth-1901.01375" aria-labelledby="oth-1901.01375">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Analysis of a Two-Layer Neural Network via Displacement Convexity </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Javanmard,+A">Adel Javanmard</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Mondelli,+M">Marco Mondelli</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Montanari,+A">Andrea Montanari</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 70 pages, 28 pdf figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1901.01477" title="Abstract" id="1901.01477"> arXiv:1901.01477 </a> [<a href="/pdf/1901.01477" title="Download PDF" id="pdf-1901.01477" aria-labelledby="pdf-1901.01477">pdf</a>, <a href="/format/1901.01477" title="Other formats" id="oth-1901.01477" aria-labelledby="oth-1901.01477">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Weylandt,+M">Michael Weylandt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nagorski,+J">John Nagorski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Allen,+G+I">Genevera I. Allen</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appear in the Journal of Computational and Graphical Statistics </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Computational and Graphical Statistics 29(1), pp. 87-96. 2020 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Computation (stat.CO); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/1901.01559" title="Abstract" id="1901.01559"> arXiv:1901.01559 </a> [<a href="/pdf/1901.01559" title="Download PDF" id="pdf-1901.01559" aria-labelledby="pdf-1901.01559">pdf</a>, <a href="/format/1901.01559" title="Other formats" id="oth-1901.01559" aria-labelledby="oth-1901.01559">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A copula based approach for electoral quick counts </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Erdely,+A">Arturo Erdely</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 3 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/1901.01583" title="Abstract" id="1901.01583"> arXiv:1901.01583 </a> [<a href="/pdf/1901.01583" title="Download PDF" id="pdf-1901.01583" aria-labelledby="pdf-1901.01583">pdf</a>, <a href="/format/1901.01583" title="Other formats" id="oth-1901.01583" aria-labelledby="oth-1901.01583">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sparse estimation for case-control studies with multiple subtypes of cases </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ballout,+N">Nadim Ballout</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Garcia,+C">Cedric Garcia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Viallon,+V">Vivian Viallon</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26 pages, 4 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> </dl> <div class='paging'>Total of 1184 entries : <span>1-50</span> <a href=/list/stat/2019-01?skip=50&show=50>51-100</a> <a href=/list/stat/2019-01?skip=100&show=50>101-150</a> <a href=/list/stat/2019-01?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2019-01?skip=1150&show=50>1151-1184</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2019-01?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2019-01?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2019-01?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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