Statistics Nov 2018

<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Nov 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/2018-11?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2018-11?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2018-11?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1811.00007" title="Abstract" id="1811.00007"> arXiv:1811.00007 </a> [<a href="/pdf/1811.00007" title="Download PDF" id="pdf-1811.00007" aria-labelledby="pdf-1811.00007">pdf</a>, <a href="/format/1811.00007" title="Other formats" id="oth-1811.00007" aria-labelledby="oth-1811.00007">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Suter,+R">Raphael Suter</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Miladinovi%C4%87,+%C4%90">膼or膽e Miladinovi膰</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sch%C3%B6lkopf,+B">Bernhard Sch枚lkopf</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bauer,+S">Stefan Bauer</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='item2'>[2]</a> <a href ="/abs/1811.00062" title="Abstract" id="1811.00062"> arXiv:1811.00062 </a> [<a href="/pdf/1811.00062" title="Download PDF" id="pdf-1811.00062" aria-labelledby="pdf-1811.00062">pdf</a>, <a href="/format/1811.00062" title="Other formats" id="oth-1811.00062" aria-labelledby="oth-1811.00062">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Interdisciplinary Comparison of Sequence Modeling Methods for Next-Element Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tax,+N">Niek Tax</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Teinemaa,+I">Irene Teinemaa</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=van+Zelst,+S+J">Sebastiaan J. van Zelst</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Computation and Language (cs.CL); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/1811.00074" title="Abstract" id="1811.00074"> arXiv:1811.00074 </a> [<a href="/pdf/1811.00074" title="Download PDF" id="pdf-1811.00074" aria-labelledby="pdf-1811.00074">pdf</a>, <a href="/format/1811.00074" title="Other formats" id="oth-1811.00074" aria-labelledby="oth-1811.00074">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Collection of Connected Vehicles Data with Precision Guarantees </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Alemazkoor,+N">Negin Alemazkoor</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meidani,+H">Hadi Meidani</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='item4'>[4]</a> <a href ="/abs/1811.00097" title="Abstract" id="1811.00097"> arXiv:1811.00097 </a> [<a href="/pdf/1811.00097" title="Download PDF" id="pdf-1811.00097" aria-labelledby="pdf-1811.00097">pdf</a>, <a href="/format/1811.00097" title="Other formats" id="oth-1811.00097" aria-labelledby="oth-1811.00097">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Evolutionary Algorithm with Crossover and Mutation for Model-Based Clustering </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=McNicholas,+S+M">Sharon M. McNicholas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=McNicholas,+P+D">Paul D. McNicholas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ashlock,+D+A">Daniel A. Ashlock</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/1811.00115" title="Abstract" id="1811.00115"> arXiv:1811.00115 </a> [<a href="/pdf/1811.00115" title="Download PDF" id="pdf-1811.00115" aria-labelledby="pdf-1811.00115">pdf</a>, <a href="/format/1811.00115" title="Other formats" id="oth-1811.00115" aria-labelledby="oth-1811.00115">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lui,+K+Y+C">Kry Yik Chau Lui</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ding,+G+W">Gavin Weiguang Ding</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Huang,+R">Ruitong Huang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=McCann,+R+J">Robert J. McCann</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montreal, Canada </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Neural Information Processing Systems (NIPS 2018) </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='item6'>[6]</a> <a href ="/abs/1811.00153" title="Abstract" id="1811.00153"> arXiv:1811.00153 </a> [<a href="/pdf/1811.00153" title="Download PDF" id="pdf-1811.00153" aria-labelledby="pdf-1811.00153">pdf</a>, <a href="/format/1811.00153" title="Other formats" id="oth-1811.00153" aria-labelledby="oth-1811.00153">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Sequential Design Approach for Calibrating a Dynamic Population Growth Model </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+R">Ru Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lin,+C+D">Chunfang Devon Lin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ranjan,+P">Pritam Ranjan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 36 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> SIAM/ASA J. Uncertainty Quantification, 7(4), 1245 -1274, 2019 </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='item7'>[7]</a> <a href ="/abs/1811.00183" title="Abstract" id="1811.00183"> arXiv:1811.00183 </a> [<a href="/pdf/1811.00183" title="Download PDF" id="pdf-1811.00183" aria-labelledby="pdf-1811.00183">pdf</a>, <a href="/format/1811.00183" title="Other formats" id="oth-1811.00183" aria-labelledby="oth-1811.00183">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Designing an Effective Metric Learning Pipeline for Speaker Diarization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Narayanaswamy,+V+S">Vivek Sivaraman Narayanaswamy</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Thiagarajan,+J+J">Jayaraman J. Thiagarajan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+H">Huan Song</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Spanias,+A">Andreas Spanias</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='item8'>[8]</a> <a href ="/abs/1811.00203" title="Abstract" id="1811.00203"> arXiv:1811.00203 </a> [<a href="/pdf/1811.00203" title="Download PDF" id="pdf-1811.00203" aria-labelledby="pdf-1811.00203">pdf</a>, <a href="/format/1811.00203" title="Other formats" id="oth-1811.00203" aria-labelledby="oth-1811.00203">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Latent Gaussian Count Time Series </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Jia,+Y">Yisu Jia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kechagias,+S">Stefanos Kechagias</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Livsey,+J">James Livsey</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lund,+R">Robert Lund</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pipiras,+V">Vladas Pipiras</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Two previous versions of this paper appeared on arxiv under the title, the first under the title "Latent Gaussian Count Time Series Modeling" and the second under the title "Count Time Series Modeling with Gaussian Copulas" </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/1811.00255" title="Abstract" id="1811.00255"> arXiv:1811.00255 </a> [<a href="/pdf/1811.00255" title="Download PDF" id="pdf-1811.00255" aria-labelledby="pdf-1811.00255">pdf</a>, <a href="/format/1811.00255" title="Other formats" id="oth-1811.00255" aria-labelledby="oth-1811.00255">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HMLasso: Lasso with High Missing Rate </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Takada,+M">Masaaki Takada</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fujisawa,+H">Hironori Fujisawa</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nishikawa,+T">Takeichiro Nishikawa</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/1811.00293" title="Abstract" id="1811.00293"> arXiv:1811.00293 </a> [<a href="/pdf/1811.00293" title="Download PDF" id="pdf-1811.00293" aria-labelledby="pdf-1811.00293">pdf</a>, <a href="/format/1811.00293" title="Other formats" id="oth-1811.00293" aria-labelledby="oth-1811.00293">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Critical initialisation for deep signal propagation in noisy rectifier neural networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Pretorius,+A">Arnu Pretorius</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Van+Biljon,+E">Elan Van Biljon</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kroon,+S">Steve Kroon</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kamper,+H">Herman Kamper</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 20 pages, 11 figures, accepted at the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018) </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='item11'>[11]</a> <a href ="/abs/1811.00306" title="Abstract" id="1811.00306"> arXiv:1811.00306 </a> [<a href="/pdf/1811.00306" title="Download PDF" id="pdf-1811.00306" aria-labelledby="pdf-1811.00306">pdf</a>, <a href="/format/1811.00306" title="Other formats" id="oth-1811.00306" aria-labelledby="oth-1811.00306">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Consistent estimation of high-dimensional factor models when the factor number is over-estimated </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Barigozzi,+M">Matteo Barigozzi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cho,+H">Haeran Cho</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='item12'>[12]</a> <a href ="/abs/1811.00314" title="Abstract" id="1811.00314"> arXiv:1811.00314 </a> [<a href="/pdf/1811.00314" title="Download PDF" id="pdf-1811.00314" aria-labelledby="pdf-1811.00314">pdf</a>, <a href="/format/1811.00314" title="Other formats" id="oth-1811.00314" aria-labelledby="oth-1811.00314">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Spatial Functional Linear Model and its Estimation Method </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Huang,+T">Tingting Huang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Saporta,+G">Gilbert Saporta</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+H">Huiwen Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+S">Shanshan Wang</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='item13'>[13]</a> <a href ="/abs/1811.00410" title="Abstract" id="1811.00410"> arXiv:1811.00410 </a> [<a href="/pdf/1811.00410" title="Download PDF" id="pdf-1811.00410" aria-labelledby="pdf-1811.00410">pdf</a>, <a href="/format/1811.00410" title="Other formats" id="oth-1811.00410" aria-labelledby="oth-1811.00410">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Dilated DenseNets for Relational Reasoning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Antoniou,+A">Antreas Antoniou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=S%C5%82owik,+A">Agnieszka S艂owik</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Crowley,+E+J">Elliot J. Crowley</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Storkey,+A">Amos Storkey</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Extended Abstract </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='item14'>[14]</a> <a href ="/abs/1811.00423" title="Abstract" id="1811.00423"> arXiv:1811.00423 </a> [<a href="/pdf/1811.00423" title="Download PDF" id="pdf-1811.00423" aria-labelledby="pdf-1811.00423">pdf</a>, <a href="/format/1811.00423" title="Other formats" id="oth-1811.00423" aria-labelledby="oth-1811.00423">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multiplicative Latent Force Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tait,+D+J">Daniel J. Tait</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Worton,+B+J">Bruce J. Worton</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='item15'>[15]</a> <a href ="/abs/1811.00439" title="Abstract" id="1811.00439"> arXiv:1811.00439 </a> [<a href="/pdf/1811.00439" title="Download PDF" id="pdf-1811.00439" aria-labelledby="pdf-1811.00439">pdf</a>, <a href="/format/1811.00439" title="Other formats" id="oth-1811.00439" aria-labelledby="oth-1811.00439">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exact parametric causal mediation analysis for a binary outcome with a binary mediator </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Doretti,+M">Marco Doretti</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Raggi,+M">Martina Raggi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Stanghellini,+E">Elena Stanghellini</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 24 pages, 5 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Statistical Methods & Applications (2021) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/1811.00450" title="Abstract" id="1811.00450"> arXiv:1811.00450 </a> [<a href="/pdf/1811.00450" title="Download PDF" id="pdf-1811.00450" aria-labelledby="pdf-1811.00450">pdf</a>, <a href="/format/1811.00450" title="Other formats" id="oth-1811.00450" aria-labelledby="oth-1811.00450">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> R friendly multi-threading in C++ </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Nagler,+T">Thomas Nagler</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='item17'>[17]</a> <a href ="/abs/1811.00457" title="Abstract" id="1811.00457"> arXiv:1811.00457 </a> [<a href="/pdf/1811.00457" title="Download PDF" id="pdf-1811.00457" aria-labelledby="pdf-1811.00457">pdf</a>, <a href="/format/1811.00457" title="Other formats" id="oth-1811.00457" aria-labelledby="oth-1811.00457">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Test & Roll: Profit-Maximizing A/B Tests </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Feit,+E+M">Elea McDonnell Feit</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Berman,+R">Ron Berman</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='item18'>[18]</a> <a href ="/abs/1811.00462" title="Abstract" id="1811.00462"> arXiv:1811.00462 </a> [<a href="/pdf/1811.00462" title="Download PDF" id="pdf-1811.00462" aria-labelledby="pdf-1811.00462">pdf</a>, <a href="/format/1811.00462" title="Other formats" id="oth-1811.00462" aria-labelledby="oth-1811.00462">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Score-Matching Representative Approach for Big Data Analysis with Generalized Linear Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+K">Keren Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+J">Jie Yang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 44 pages, 11 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='item19'>[19]</a> <a href ="/abs/1811.00465" title="Abstract" id="1811.00465"> arXiv:1811.00465 </a> [<a href="/pdf/1811.00465" title="Download PDF" id="pdf-1811.00465" aria-labelledby="pdf-1811.00465">pdf</a>, <a href="/format/1811.00465" title="Other formats" id="oth-1811.00465" aria-labelledby="oth-1811.00465">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Brunel,+V">Victor-Emmanuel Brunel</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Shorter version accepted at NIPS (Neural Information Processing Systems) 2018 </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='item20'>[20]</a> <a href ="/abs/1811.00488" title="Abstract" id="1811.00488"> arXiv:1811.00488 </a> [<a href="/pdf/1811.00488" title="Download PDF" id="pdf-1811.00488" aria-labelledby="pdf-1811.00488">pdf</a>, <a href="/format/1811.00488" title="Other formats" id="oth-1811.00488" aria-labelledby="oth-1811.00488">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sparse Model Identification and Learning for Ultra-high-dimensional Additive Partially Linear Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+X">Xinyi Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+L">Li Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nettleton,+D">Dan Nettleton</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Multivariate Analysis, 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/1811.00512" title="Abstract" id="1811.00512"> arXiv:1811.00512 </a> [<a href="/pdf/1811.00512" title="Download PDF" id="pdf-1811.00512" aria-labelledby="pdf-1811.00512">pdf</a>, <a href="/format/1811.00512" title="Other formats" id="oth-1811.00512" aria-labelledby="oth-1811.00512">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Beam Search Policies via Imitation Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Negrinho,+R">Renato Negrinho</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gormley,+M+R">Matthew R. Gormley</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gordon,+G+J">Geoffrey J. Gordon</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published in NIPS 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='item22'>[22]</a> <a href ="/abs/1811.00535" title="Abstract" id="1811.00535"> arXiv:1811.00535 </a> [<a href="/pdf/1811.00535" title="Download PDF" id="pdf-1811.00535" aria-labelledby="pdf-1811.00535">pdf</a>, <a href="/format/1811.00535" title="Other formats" id="oth-1811.00535" aria-labelledby="oth-1811.00535">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> High Dimensional Robust Inference for Cox Regression Models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kong,+S">Shengchun Kong</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Yu,+Z">Zhuqing Yu</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Zhang,+X">Xianyang Zhang</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Cheng,+G">Guang Cheng</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='item23'>[23]</a> <a href ="/abs/1811.00542" title="Abstract" id="1811.00542"> arXiv:1811.00542 </a> [<a href="/pdf/1811.00542" title="Download PDF" id="pdf-1811.00542" aria-labelledby="pdf-1811.00542">pdf</a>, <a href="/format/1811.00542" title="Other formats" id="oth-1811.00542" aria-labelledby="oth-1811.00542">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Pymc-learn: Practical Probabilistic Machine Learning in Python </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Emaasit,+D">Daniel Emaasit</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/1811.00591" title="Abstract" id="1811.00591"> arXiv:1811.00591 </a> [<a href="/pdf/1811.00591" title="Download PDF" id="pdf-1811.00591" aria-labelledby="pdf-1811.00591">pdf</a>, <a href="/format/1811.00591" title="Other formats" id="oth-1811.00591" aria-labelledby="oth-1811.00591">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Defining a Metric Space of Host Logs and Operational Use Cases </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Verma,+M+E">Miki E. Verma</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bridges,+R+A">Robert A. Bridges</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Cryptography and Security (cs.CR) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/1811.00596" title="Abstract" id="1811.00596"> arXiv:1811.00596 </a> [<a href="/pdf/1811.00596" title="Download PDF" id="pdf-1811.00596" aria-labelledby="pdf-1811.00596">pdf</a>, <a href="/format/1811.00596" title="Other formats" id="oth-1811.00596" aria-labelledby="oth-1811.00596">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Variational Dropout via Empirical Bayes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kharitonov,+V">Valery Kharitonov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Molchanov,+D">Dmitry Molchanov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vetrov,+D">Dmitry Vetrov</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='item26'>[26]</a> <a href ="/abs/1811.00628" title="Abstract" id="1811.00628"> arXiv:1811.00628 </a> [<a href="/pdf/1811.00628" title="Download PDF" id="pdf-1811.00628" aria-labelledby="pdf-1811.00628">pdf</a>, <a href="/format/1811.00628" title="Other formats" id="oth-1811.00628" aria-labelledby="oth-1811.00628">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Boukouvalas,+Z">Zois Boukouvalas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Elton,+D+C">Daniel C. Elton</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chung,+P+W">Peter W. Chung</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fuge,+M+D">Mark D. Fuge</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Materials Science (cond-mat.mtrl-sci); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/1811.00631" title="Abstract" id="1811.00631"> arXiv:1811.00631 </a> [<a href="/pdf/1811.00631" title="Download PDF" id="pdf-1811.00631" aria-labelledby="pdf-1811.00631">pdf</a>, <a href="/format/1811.00631" title="Other formats" id="oth-1811.00631" aria-labelledby="oth-1811.00631">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MDFS - MultiDimensional Feature Selection </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Piliszek,+R">Rados艂aw Piliszek</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mnich,+K">Krzysztof Mnich</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Migacz,+S">Szymon Migacz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tabaszewski,+P">Pawe艂 Tabaszewski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Su%C5%82ecki,+A">Andrzej Su艂ecki</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Polewko-Klim,+A">Aneta Polewko-Klim</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rudnicki,+W">Witold Rudnicki</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 12 pages, 3 figures, 5 tables, license: CC-BY </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='item28'>[28]</a> <a href ="/abs/1811.00638" title="Abstract" id="1811.00638"> arXiv:1811.00638 </a> [<a href="/pdf/1811.00638" title="Download PDF" id="pdf-1811.00638" aria-labelledby="pdf-1811.00638">pdf</a>, <a href="/format/1811.00638" title="Other formats" id="oth-1811.00638" aria-labelledby="oth-1811.00638">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Simple Sensitivity Analysis for Differential Measurement Error </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=VanderWeele,+T+J">Tyler J. VanderWeele</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Y">Yige Li</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='item29'>[29]</a> <a href ="/abs/1811.00645" title="Abstract" id="1811.00645"> arXiv:1811.00645 </a> [<a href="/pdf/1811.00645" title="Download PDF" id="pdf-1811.00645" aria-labelledby="pdf-1811.00645">pdf</a>, <a href="/format/1811.00645" title="Other formats" id="oth-1811.00645" aria-labelledby="oth-1811.00645">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Holdout Randomization Test for Feature Selection in Black Box Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tansey,+W">Wesley Tansey</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Veitch,+V">Victor Veitch</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+H">Haoran Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rabadan,+R">Raul Rabadan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Blei,+D+M">David M. Blei</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> New algorithms and simulations; accepted for publication at JCGS </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/1811.00673" title="Abstract" id="1811.00673"> arXiv:1811.00673 </a> [<a href="/pdf/1811.00673" title="Download PDF" id="pdf-1811.00673" aria-labelledby="pdf-1811.00673">pdf</a>, <a href="/format/1811.00673" title="Other formats" id="oth-1811.00673" aria-labelledby="oth-1811.00673">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Ludometrics: Luck, and How to Measure It </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gilbert,+D+E">Daniel E. Gilbert</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wells,+M+T">Martin T. Wells</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='item31'>[31]</a> <a href ="/abs/1811.00683" title="Abstract" id="1811.00683"> arXiv:1811.00683 </a> [<a href="/pdf/1811.00683" title="Download PDF" id="pdf-1811.00683" aria-labelledby="pdf-1811.00683">pdf</a>, <a href="/format/1811.00683" title="Other formats" id="oth-1811.00683" aria-labelledby="oth-1811.00683">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Quasi-random sampling for multivariate distributions via generative neural networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hofert,+M">Marius Hofert</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Prasad,+A">Avinash Prasad</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhu,+M">Mu Zhu</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/1811.00686" title="Abstract" id="1811.00686"> arXiv:1811.00686 </a> [<a href="/pdf/1811.00686" title="Download PDF" id="pdf-1811.00686" aria-labelledby="pdf-1811.00686">pdf</a>, <a href="/format/1811.00686" title="Other formats" id="oth-1811.00686" aria-labelledby="oth-1811.00686">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Jankowiak,+M">Martin Jankowiak</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Bayesian Deep Learning Workshop @ NeurIPS 2018; 11 pages </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='item33'>[33]</a> <a href ="/abs/1811.00722" title="Abstract" id="1811.00722"> arXiv:1811.00722 </a> [<a href="/pdf/1811.00722" title="Download PDF" id="pdf-1811.00722" aria-labelledby="pdf-1811.00722">pdf</a>, <a href="/format/1811.00722" title="Other formats" id="oth-1811.00722" aria-labelledby="oth-1811.00722">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Adaptive MCMC for Generalized Method of Moments with Many Moment Conditions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tanaka,+M">Masahiro Tanaka</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='item34'>[34]</a> <a href ="/abs/1811.00724" title="Abstract" id="1811.00724"> arXiv:1811.00724 </a> [<a href="/pdf/1811.00724" title="Download PDF" id="pdf-1811.00724" aria-labelledby="pdf-1811.00724">pdf</a>, <a href="/format/1811.00724" title="Other formats" id="oth-1811.00724" aria-labelledby="oth-1811.00724">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Hierarchical Modeling on Covariance Valued Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Acharyya,+S">Satwik Acharyya</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+Z">Zhengwu Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bhattacharya,+A">Anirban Bhattacharya</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pati,+D">Debdeep Pati</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Some key references are missing in the old version which are corrected in this version </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/1811.00731" title="Abstract" id="1811.00731"> arXiv:1811.00731 </a> [<a href="/pdf/1811.00731" title="Download PDF" id="pdf-1811.00731" aria-labelledby="pdf-1811.00731">pdf</a>, <a href="/format/1811.00731" title="Other formats" id="oth-1811.00731" aria-labelledby="oth-1811.00731">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The age of secrecy and unfairness in recidivism prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rudin,+C">Cynthia Rudin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+C">Caroline Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Coker,+B">Beau Coker</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Harvard Data Science Review 2(1), 2020 </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='item36'>[36]</a> <a href ="/abs/1811.00741" title="Abstract" id="1811.00741"> arXiv:1811.00741 </a> [<a href="/pdf/1811.00741" title="Download PDF" id="pdf-1811.00741" aria-labelledby="pdf-1811.00741">pdf</a>, <a href="/format/1811.00741" title="Other formats" id="oth-1811.00741" aria-labelledby="oth-1811.00741">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Stronger Data Poisoning Attacks Break Data Sanitization Defenses </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Koh,+P+W">Pang Wei Koh</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Steinhardt,+J">Jacob Steinhardt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Liang,+P">Percy Liang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This paper was first published on arXiv in 2018 and has since been edited for clarity </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Machine Learning, 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Cryptography and Security (cs.CR); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/1811.00781" title="Abstract" id="1811.00781"> arXiv:1811.00781 </a> [<a href="/pdf/1811.00781" title="Download PDF" id="pdf-1811.00781" aria-labelledby="pdf-1811.00781">pdf</a>, <a href="/format/1811.00781" title="Other formats" id="oth-1811.00781" aria-labelledby="oth-1811.00781">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Non-Asymptotic Guarantees For Sampling by Stochastic Gradient Descent </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Karagulyan,+A">Avetik Karagulyan</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='item38'>[38]</a> <a href ="/abs/1811.00782" title="Abstract" id="1811.00782"> arXiv:1811.00782 </a> [<a href="/pdf/1811.00782" title="Download PDF" id="pdf-1811.00782" aria-labelledby="pdf-1811.00782">pdf</a>, <a href="/format/1811.00782" title="Other formats" id="oth-1811.00782" aria-labelledby="oth-1811.00782">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Multiplicative Mixed Model with the mumm R package as a General and Easy Random Interaction Model Tool </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=P%C3%B8denphant,+S">Sofie P酶denphant</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kristensen,+K">Kasper Kristensen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Brockhoff,+P+B">Per B. Brockhoff</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='item39'>[39]</a> <a href ="/abs/1811.00908" title="Abstract" id="1811.00908"> arXiv:1811.00908 </a> [<a href="/pdf/1811.00908" title="Download PDF" id="pdf-1811.00908" aria-labelledby="pdf-1811.00908">pdf</a>, <a href="/format/1811.00908" title="Other formats" id="oth-1811.00908" aria-labelledby="oth-1811.00908">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Single-Model Uncertainties for Deep Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Tagasovska,+N">Natasa Tagasovska</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lopez-Paz,+D">David Lopez-Paz</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appear in NeurIPS 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='item40'>[40]</a> <a href ="/abs/1811.00928" title="Abstract" id="1811.00928"> arXiv:1811.00928 </a> [<a href="/pdf/1811.00928" title="Download PDF" id="pdf-1811.00928" aria-labelledby="pdf-1811.00928">pdf</a>, <a href="/format/1811.00928" title="Other formats" id="oth-1811.00928" aria-labelledby="oth-1811.00928">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Foundations of Comparison-Based Hierarchical Clustering </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ghoshdastidar,+D">Debarghya Ghoshdastidar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Perrot,+M">Micha毛l Perrot</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=von+Luxburg,+U">Ulrike von Luxburg</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26 pages </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='item41'>[41]</a> <a href ="/abs/1811.00934" title="Abstract" id="1811.00934"> arXiv:1811.00934 </a> [<a href="/pdf/1811.00934" title="Download PDF" id="pdf-1811.00934" aria-labelledby="pdf-1811.00934">pdf</a>, <a href="/format/1811.00934" title="Other formats" id="oth-1811.00934" aria-labelledby="oth-1811.00934">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonparametric identification in the dynamic stochastic block model </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Becker,+A">Ann-Kristin Becker</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Holzmann,+H">Hajo Holzmann</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/1811.00956" title="Abstract" id="1811.00956"> arXiv:1811.00956 </a> [<a href="/pdf/1811.00956" title="Download PDF" id="pdf-1811.00956" aria-labelledby="pdf-1811.00956">pdf</a>, <a href="/format/1811.00956" title="Other formats" id="oth-1811.00956" aria-labelledby="oth-1811.00956">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Fast Algorithm for Clustering High Dimensional Feature Vectors </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rahman,+S">Shahina Rahman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Johnson,+V+E">Valen E. Johnson</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='item43'>[43]</a> <a href ="/abs/1811.00964" title="Abstract" id="1811.00964"> arXiv:1811.00964 </a> [<a href="/pdf/1811.00964" title="Download PDF" id="pdf-1811.00964" aria-labelledby="pdf-1811.00964">pdf</a>, <a href="/format/1811.00964" title="Other formats" id="oth-1811.00964" aria-labelledby="oth-1811.00964">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The X Factor: A Robust and Powerful Approach to X-chromosome-Inclusive Whole-genome Association Studies </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+B">Bo Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Craiu,+R+V">Radu V. Craiu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Strug,+L+J">Lisa J. Strug</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sun,+L">Lei Sun</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='item44'>[44]</a> <a href ="/abs/1811.00974" title="Abstract" id="1811.00974"> arXiv:1811.00974 </a> [<a href="/pdf/1811.00974" title="Download PDF" id="pdf-1811.00974" aria-labelledby="pdf-1811.00974">pdf</a>, <a href="/format/1811.00974" title="Other formats" id="oth-1811.00974" aria-labelledby="oth-1811.00974">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural Likelihoods via Cumulative Distribution Functions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chilinski,+P">Pawel Chilinski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Silva,+R">Ricardo Silva</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 pages </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/1811.01061" title="Abstract" id="1811.01061"> arXiv:1811.01061 </a> [<a href="/pdf/1811.01061" title="Download PDF" id="pdf-1811.01061" aria-labelledby="pdf-1811.01061">pdf</a>, <a href="/format/1811.01061" title="Other formats" id="oth-1811.01061" aria-labelledby="oth-1811.01061">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The Goldenshluger-Lepski Method for Constrained Least-Squares Estimators over RKHSs </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Page,+S">Stephen Page</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Gr%C3%BCnew%C3%A4lder,+S">Steffen Gr眉new盲lder</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 50 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='item46'>[46]</a> <a href ="/abs/1811.01076" title="Abstract" id="1811.01076"> arXiv:1811.01076 </a> [<a href="/pdf/1811.01076" title="Download PDF" id="pdf-1811.01076" aria-labelledby="pdf-1811.01076">pdf</a>, <a href="/format/1811.01076" title="Other formats" id="oth-1811.01076" aria-labelledby="oth-1811.01076">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Shah,+R+D">Rajen D. Shah</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Frot,+B">Benjamin Frot</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Thanei,+G">Gian-Andrea Thanei</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meinshausen,+N">Nicolai Meinshausen</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 49 pages; to appear in JRSSB </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='item47'>[47]</a> <a href ="/abs/1811.01091" title="Abstract" id="1811.01091"> arXiv:1811.01091 </a> [<a href="/pdf/1811.01091" title="Download PDF" id="pdf-1811.01091" aria-labelledby="pdf-1811.01091">pdf</a>, <a href="/format/1811.01091" title="Other formats" id="oth-1811.01091" aria-labelledby="oth-1811.01091">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Saibaba,+A+K">Arvind K. Saibaba</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bardsley,+J">Johnathan Bardsley</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Brown,+D+A">D. Andrew Brown</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Alexanderian,+A">Alen Alexanderian</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 8 figures, 5 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Numerical Analysis (math.NA) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1811.01117" title="Abstract" id="1811.01117"> arXiv:1811.01117 </a> [<a href="/pdf/1811.01117" title="Download PDF" id="pdf-1811.01117" aria-labelledby="pdf-1811.01117">pdf</a>, <a href="/format/1811.01117" title="Other formats" id="oth-1811.01117" aria-labelledby="oth-1811.01117">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Semiparametric Mixture Regression with Unspecified Error Distributions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ma,+Y">Yanyuan Ma</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+S">Shaoli Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+L">Lin Xu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yao,+W">Weixin Yao</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/1811.01159" title="Abstract" id="1811.01159"> arXiv:1811.01159 </a> [<a href="/pdf/1811.01159" title="Download PDF" id="pdf-1811.01159" aria-labelledby="pdf-1811.01159">pdf</a>, <a href="/format/1811.01159" title="Other formats" id="oth-1811.01159" aria-labelledby="oth-1811.01159">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Understanding and Comparing Scalable Gaussian Process Regression for Big Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+H">Haitao Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cai,+J">Jianfei Cai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ong,+Y">Yew-Soon Ong</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yi Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 pages, 15 figures, preprint submitted to KBS </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='item50'>[50]</a> <a href ="/abs/1811.01179" title="Abstract" id="1811.01179"> arXiv:1811.01179 </a> [<a href="/pdf/1811.01179" title="Download PDF" id="pdf-1811.01179" aria-labelledby="pdf-1811.01179">pdf</a>, <a href="/format/1811.01179" title="Other formats" id="oth-1811.01179" aria-labelledby="oth-1811.01179">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large-scale Heteroscedastic Regression via Gaussian Process </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+H">Haitao Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ong,+Y">Yew-Soon Ong</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cai,+J">Jianfei Cai</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 14 pages, 15 figures </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> </dl> <div class='paging'>Total of 1260 entries : <span>1-50</span> <a href=/list/stat/2018-11?skip=50&show=50>51-100</a> <a href=/list/stat/2018-11?skip=100&show=50>101-150</a> <a href=/list/stat/2018-11?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2018-11?skip=1250&show=50>1251-1260</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2018-11?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2018-11?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2018-11?skip=0&show=2000 rel="nofollow"> all</a> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; 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