Statistics Dec 2016

<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Dec 2016</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/2016-12?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2016-12?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2016-12?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1612.00040" title="Abstract" id="1612.00040"> arXiv:1612.00040 </a> [<a href="/pdf/1612.00040" title="Download PDF" id="pdf-1612.00040" aria-labelledby="pdf-1612.00040">pdf</a>, <a href="/format/1612.00040" title="Other formats" id="oth-1612.00040" aria-labelledby="oth-1612.00040">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Principal component analysis of periodically correlated functional time series </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kidzi%C5%84ski,+%C5%81">艁ukasz Kidzi艅ski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kokoszka,+P">Piotr Kokoszka</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jouzdani,+N+M">Neda Mohammadi Jouzdani</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 31 pages, 4 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='item2'>[2]</a> <a href ="/abs/1612.00064" title="Abstract" id="1612.00064"> arXiv:1612.00064 </a> [<a href="/pdf/1612.00064" title="Download PDF" id="pdf-1612.00064" aria-labelledby="pdf-1612.00064">pdf</a>, <a href="/format/1612.00064" title="Other formats" id="oth-1612.00064" aria-labelledby="oth-1612.00064">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Objective Priors in the Empirical Bayes Framework </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Klebanov,+I">Ilja Klebanov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sikorski,+A">Alexander Sikorski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sch%C3%BCtte,+C">Christof Sch眉tte</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=R%C3%B6blitz,+S">Susanna R枚blitz</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/1612.00068" title="Abstract" id="1612.00068"> arXiv:1612.00068 </a> [<a href="/pdf/1612.00068" title="Download PDF" id="pdf-1612.00068" aria-labelledby="pdf-1612.00068">pdf</a>, <a href="/format/1612.00068" title="Other formats" id="oth-1612.00068" aria-labelledby="oth-1612.00068">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Efficient Estimation in Single Index Models through Smoothing splines </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kuchibhotla,+A+K">Arun Kumar Kuchibhotla</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Patra,+R+K">Rohit Kumar Patra</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 50 pages, 3 figures, and 2 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/1612.00081" title="Abstract" id="1612.00081"> arXiv:1612.00081 </a> [<a href="/pdf/1612.00081" title="Download PDF" id="pdf-1612.00081" aria-labelledby="pdf-1612.00081">pdf</a>, <a href="/format/1612.00081" title="Other formats" id="oth-1612.00081" aria-labelledby="oth-1612.00081">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Two Methods For Wild Variational Inference </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+Q">Qiang Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Feng,+Y">Yihao Feng</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/1612.00083" title="Abstract" id="1612.00083"> arXiv:1612.00083 </a> [<a href="/pdf/1612.00083" title="Download PDF" id="pdf-1612.00083" aria-labelledby="pdf-1612.00083">pdf</a>, <a href="/format/1612.00083" title="Other formats" id="oth-1612.00083" aria-labelledby="oth-1612.00083">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Model based approach for household clustering with mixed scale variables </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Carmona,+C">Christian Carmona</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nieto-Barajas,+L">Luis Nieto-Barajas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Canale,+A">Antonio Canale</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Computation (stat.CO) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/1612.00099" title="Abstract" id="1612.00099"> arXiv:1612.00099 </a> [<a href="/pdf/1612.00099" title="Download PDF" id="pdf-1612.00099" aria-labelledby="pdf-1612.00099">pdf</a>, <a href="/format/1612.00099" title="Other formats" id="oth-1612.00099" aria-labelledby="oth-1612.00099">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> PAG2ADMG: An Algorithm for the Complete Causal Enumeration of a Markov Equivalence Class </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Subramani,+N">Nishant Subramani</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> V2 and V1 are different enough to be different papers. V2 will be significantly extended and resubmitted as a different arxiv paper </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/1612.00111" title="Abstract" id="1612.00111"> arXiv:1612.00111 </a> [<a href="/pdf/1612.00111" title="Download PDF" id="pdf-1612.00111" aria-labelledby="pdf-1612.00111">pdf</a>, <a href="/format/1612.00111" title="Other formats" id="oth-1612.00111" aria-labelledby="oth-1612.00111">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Non-parametric Simultaneous Quantile Regression for Complete and Grid Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Das,+P">Priyam Das</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ghosal,+S">Subhashis Ghosal</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 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='item8'>[8]</a> <a href ="/abs/1612.00129" title="Abstract" id="1612.00129"> arXiv:1612.00129 </a> [<a href="/pdf/1612.00129" title="Download PDF" id="pdf-1612.00129" aria-labelledby="pdf-1612.00129">pdf</a>, <a href="/format/1612.00129" title="Other formats" id="oth-1612.00129" aria-labelledby="oth-1612.00129">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Predicting Long-term Outcomes of Educational Interventions Using the Evolutionary Causal Matrices and Markov Chain Based on Educational Neuroscience </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Han,+H">Hyemin Han</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lee,+K">Kangwook Lee</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Soylu,+F">Firat Soylu</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Trends.Neurosci.Educ. 5 (2016) 157-165 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/1612.00136" title="Abstract" id="1612.00136"> arXiv:1612.00136 </a> [<a href="/pdf/1612.00136" title="Download PDF" id="pdf-1612.00136" aria-labelledby="pdf-1612.00136">pdf</a>, <a href="/format/1612.00136" title="Other formats" id="oth-1612.00136" aria-labelledby="oth-1612.00136">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Estimation and Model Identification of Locally Stationary Varying-Coefficient Additive Models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Hu,+L">Lixia Hu</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Huang,+T">Tao Huang</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=You,+J">Jinhong You</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 36 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='item10'>[10]</a> <a href ="/abs/1612.00196" title="Abstract" id="1612.00196"> arXiv:1612.00196 </a> [<a href="/pdf/1612.00196" title="Download PDF" id="pdf-1612.00196" aria-labelledby="pdf-1612.00196">pdf</a>, <a href="/format/1612.00196" title="Other formats" id="oth-1612.00196" aria-labelledby="oth-1612.00196">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Estimating a monotone probability mass function with known flat regions </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Anevski,+D">Dragi Anevski</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Pastukhov,+V+M">Vladimir M. Pastukhov</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, 1 figure </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='item11'>[11]</a> <a href ="/abs/1612.00259" title="Abstract" id="1612.00259"> arXiv:1612.00259 </a> [<a href="/pdf/1612.00259" title="Download PDF" id="pdf-1612.00259" aria-labelledby="pdf-1612.00259">pdf</a>, <a href="/format/1612.00259" title="Other formats" id="oth-1612.00259" aria-labelledby="oth-1612.00259">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> rCOSA: A Software Package for Clustering Objects on Subsets of Attributes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kampert,+M+M">Maarten M. Kampert</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meulman,+J+J">Jacqueline J. Meulman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Friedman,+J+H">Jerome H. Friedman</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for publication by the Journal of Classification </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/1612.00328" title="Abstract" id="1612.00328"> arXiv:1612.00328 </a> [<a href="/pdf/1612.00328" title="Download PDF" id="pdf-1612.00328" aria-labelledby="pdf-1612.00328">pdf</a>, <a href="/format/1612.00328" title="Other formats" id="oth-1612.00328" aria-labelledby="oth-1612.00328">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal discrimination designs for semi-parametric models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Dette,+H">Holger Dette</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Guchenko,+R">Roman Guchenko</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Melas,+V">Viatcheslav Melas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wong,+W+K">Weng Kee Wong</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/1612.00374" title="Abstract" id="1612.00374"> arXiv:1612.00374 </a> [<a href="/pdf/1612.00374" title="Download PDF" id="pdf-1612.00374" aria-labelledby="pdf-1612.00374">pdf</a>, <a href="/format/1612.00374" title="Other formats" id="oth-1612.00374" aria-labelledby="oth-1612.00374">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Spatial Decompositions for Large Scale SVMs </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Thomann,+P">Philipp Thomann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Blaschzyk,+I">Ingrid Blaschzyk</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meister,+M">Mona Meister</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Steinwart,+I">Ingo Steinwart</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Proceedings of Machine Learning Research Volume 54: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics 2017 (A. Singh and J. Zhu, eds.), pp. 1329-1337, 2017 </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/1612.00383" title="Abstract" id="1612.00383"> arXiv:1612.00383 </a> [<a href="/pdf/1612.00383" title="Download PDF" id="pdf-1612.00383" aria-labelledby="pdf-1612.00383">pdf</a>, <a href="/format/1612.00383" title="Other formats" id="oth-1612.00383" aria-labelledby="oth-1612.00383">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Dalibard,+V">Valentin Dalibard</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Schaarschmidt,+M">Michael Schaarschmidt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yoneki,+E">Eiko Yoneki</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/1612.00388" title="Abstract" id="1612.00388"> arXiv:1612.00388 </a> [<a href="/pdf/1612.00388" title="Download PDF" id="pdf-1612.00388" aria-labelledby="pdf-1612.00388">pdf</a>, <a href="/format/1612.00388" title="Other formats" id="oth-1612.00388" aria-labelledby="oth-1612.00388">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Diet2Vec: Multi-scale analysis of massive dietary data </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=Lowe,+E+W">Edward W. Lowe Jr.</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Scott,+J+G">James G. Scott</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted to the NIPS 2016 Workshop on Machine Learning for Health </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Applications (stat.AP) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/1612.00393" title="Abstract" id="1612.00393"> arXiv:1612.00393 </a> [<a href="/pdf/1612.00393" title="Download PDF" id="pdf-1612.00393" aria-labelledby="pdf-1612.00393">pdf</a>, <a href="/format/1612.00393" title="Other formats" id="oth-1612.00393" aria-labelledby="oth-1612.00393">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Hypervolume-based Multi-objective Bayesian Optimization with Student-t Processes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=van+der+Herten,+J">Joachim van der Herten</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Couckuyt,+I">Ivo Couckuyt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dhaene,+T">Tom Dhaene</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 3 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> <dt> <a name='item17'>[17]</a> <a href ="/abs/1612.00424" title="Abstract" id="1612.00424"> arXiv:1612.00424 </a> [<a href="/pdf/1612.00424" title="Download PDF" id="pdf-1612.00424" aria-labelledby="pdf-1612.00424">pdf</a>, <a href="/format/1612.00424" title="Other formats" id="oth-1612.00424" aria-labelledby="oth-1612.00424">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Doubly robust matching estimators for high dimensional confounding adjustment </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Antonelli,+J">Joseph Antonelli</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cefalu,+M">Matthew Cefalu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Palmer,+N">Nathan Palmer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Agniel,+D">Denis Agniel</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='item18'>[18]</a> <a href ="/abs/1612.00475" title="Abstract" id="1612.00475"> arXiv:1612.00475 </a> [<a href="/pdf/1612.00475" title="Download PDF" id="pdf-1612.00475" aria-labelledby="pdf-1612.00475">pdf</a>, <a href="/format/1612.00475" title="Other formats" id="oth-1612.00475" aria-labelledby="oth-1612.00475">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Killian,+T">Taylor Killian</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Konidaris,+G">George Konidaris</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Doshi-Velez,+F">Finale Doshi-Velez</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Brief abstract for poster submission to Machine Learning for Healthcare workshop at NIPS 2016 </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='item19'>[19]</a> <a href ="/abs/1612.00497" title="Abstract" id="1612.00497"> arXiv:1612.00497 </a> [<a href="/pdf/1612.00497" title="Download PDF" id="pdf-1612.00497" aria-labelledby="pdf-1612.00497">pdf</a>, <a href="/format/1612.00497" title="Other formats" id="oth-1612.00497" aria-labelledby="oth-1612.00497">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Opioid Atlas: Mapping Access to Pain Medication </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Sankaran,+K">Kris Sankaran</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tamang,+S">Suzanne Tamang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bhatt,+A">Ami Bhatt</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='item20'>[20]</a> <a href ="/abs/1612.00503" title="Abstract" id="1612.00503"> arXiv:1612.00503 </a> [<a href="/pdf/1612.00503" title="Download PDF" id="pdf-1612.00503" aria-labelledby="pdf-1612.00503">pdf</a>, <a href="/format/1612.00503" title="Other formats" id="oth-1612.00503" aria-labelledby="oth-1612.00503">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multibrand geographic experiments </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Owen,+A+B">Art B. Owen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Launay,+T">Tristan Launay</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='item21'>[21]</a> <a href ="/abs/1612.00516" title="Abstract" id="1612.00516"> arXiv:1612.00516 </a> [<a href="/pdf/1612.00516" title="Download PDF" id="pdf-1612.00516" aria-labelledby="pdf-1612.00516">pdf</a>, <a href="/format/1612.00516" title="Other formats" id="oth-1612.00516" aria-labelledby="oth-1612.00516">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Canonical Correlation Analysis for Analyzing Sequences of Medical Billing Codes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Jones,+C+L">Corinne L. Jones</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kakade,+S+M">Sham M. Kakade</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Thornblade,+L+W">Lucas W. Thornblade</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Flum,+D+R">David R. Flum</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Flaxman,+A+D">Abraham D. Flaxman</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at NIPS 2016 Workshop on Machine Learning for Health </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/1612.00520" title="Abstract" id="1612.00520"> arXiv:1612.00520 </a> [<a href="/pdf/1612.00520" title="Download PDF" id="pdf-1612.00520" aria-labelledby="pdf-1612.00520">pdf</a>, <a href="/format/1612.00520" title="Other formats" id="oth-1612.00520" aria-labelledby="oth-1612.00520">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian Approach to Predicting Disengaged Youth </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kohn,+D">David Kohn</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cripps,+S">Sally Cripps</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Glozier,+N">Nick Glozier</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Durrant-Whyte,+H">Hugh Durrant-Whyte</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 2 figures, 2 tables, NIPS 2016 Workshop on Machine Learning for Health </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/1612.00549" title="Abstract" id="1612.00549"> arXiv:1612.00549 </a> [<a href="/pdf/1612.00549" title="Download PDF" id="pdf-1612.00549" aria-labelledby="pdf-1612.00549">pdf</a>, <a href="/format/1612.00549" title="Other formats" id="oth-1612.00549" aria-labelledby="oth-1612.00549">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MF is always superior to CEM </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Geng,+X">Xiurui Geng</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ji,+L">Luyan Ji</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+W">Weitun Yang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+F">Fuxiang Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+Y">Yongchao Zhao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 4 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='item24'>[24]</a> <a href ="/abs/1612.00555" title="Abstract" id="1612.00555"> arXiv:1612.00555 </a> [<a href="/pdf/1612.00555" title="Download PDF" id="pdf-1612.00555" aria-labelledby="pdf-1612.00555">pdf</a>, <a href="/format/1612.00555" title="Other formats" id="oth-1612.00555" aria-labelledby="oth-1612.00555">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Transfer Learning via Latent Factor Modeling to Improve Prediction of Surgical Complications </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lorenzi,+E+C">Elizabeth C Lorenzi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sun,+Z">Zhifei Sun</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Huang,+E">Erich Huang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Henao,+R">Ricardo Henao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Heller,+K+A">Katherine A Heller</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/1612.00571" title="Abstract" id="1612.00571"> arXiv:1612.00571 </a> [<a href="/pdf/1612.00571" title="Download PDF" id="pdf-1612.00571" aria-labelledby="pdf-1612.00571">pdf</a>, <a href="/format/1612.00571" title="Other formats" id="oth-1612.00571" aria-labelledby="oth-1612.00571">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reliability study of series and parallel systems of heterogeneous component lifetimes under proportional odds model </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kundu,+P">Pradip Kundu</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Hazra,+N+K">Nil Kamal Hazra</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Nanda,+A+K">Asok K. Nanda</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 30 pages, 7 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Statistics 54(2) (2020) 375-401 </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='item26'>[26]</a> <a href ="/abs/1612.00583" title="Abstract" id="1612.00583"> arXiv:1612.00583 </a> [<a href="/pdf/1612.00583" title="Download PDF" id="pdf-1612.00583" aria-labelledby="pdf-1612.00583">pdf</a>, <a href="/format/1612.00583" title="Other formats" id="oth-1612.00583" aria-labelledby="oth-1612.00583">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Active Search for Sparse Signals with Region Sensing </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ma,+Y">Yifei Ma</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Garnett,+R">Roman Garnett</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Schneider,+J">Jeff Schneider</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> aaai 2017 preprint; nips exhibition of rejections </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='item27'>[27]</a> <a href ="/abs/1612.00595" title="Abstract" id="1612.00595"> arXiv:1612.00595 </a> [<a href="/pdf/1612.00595" title="Download PDF" id="pdf-1612.00595" aria-labelledby="pdf-1612.00595">pdf</a>, <a href="/format/1612.00595" title="Other formats" id="oth-1612.00595" aria-labelledby="oth-1612.00595">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Parallel Chromatic MCMC with Spatial Partitioning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+J">Jun Song</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Moore,+D+A">David A. Moore</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/1612.00615" title="Abstract" id="1612.00615"> arXiv:1612.00615 </a> [<a href="/pdf/1612.00615" title="Download PDF" id="pdf-1612.00615" aria-labelledby="pdf-1612.00615">pdf</a>, <a href="/format/1612.00615" title="Other formats" id="oth-1612.00615" aria-labelledby="oth-1612.00615">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A temporal model for multiple sclerosis course evolution </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Fiorini,+S">Samuele Fiorini</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tacchino,+A">Andrea Tacchino</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Brichetto,+G">Giampaolo Brichetto</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Verri,+A">Alessandro Verri</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Barla,+A">Annalisa Barla</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NIPS Machine Learning for health Workshop 2016 </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='item29'>[29]</a> <a href ="/abs/1612.00662" title="Abstract" id="1612.00662"> arXiv:1612.00662 </a> [<a href="/pdf/1612.00662" title="Download PDF" id="pdf-1612.00662" aria-labelledby="pdf-1612.00662">pdf</a>, <a href="/format/1612.00662" title="Other formats" id="oth-1612.00662" aria-labelledby="oth-1612.00662">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=McCarthy,+A">Adam McCarthy</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Williams,+C+K">Christopher K.I. Williams</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> NIPS 2016 Workshop on Machine Learning for Health </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='item30'>[30]</a> <a href ="/abs/1612.00664" title="Abstract" id="1612.00664"> arXiv:1612.00664 </a> [<a href="/pdf/1612.00664" title="Download PDF" id="pdf-1612.00664" aria-labelledby="pdf-1612.00664">pdf</a>, <a href="/format/1612.00664" title="Other formats" id="oth-1612.00664" aria-labelledby="oth-1612.00664">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Survival Prediction with Limited Features: a Top Performing Approach from the DREAM ALS Stratification Prize4Life Challenge </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kurz,+C">Christoph Kurz</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> accepted for NIPS 2016 ML4HC workshop </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Quantitative Methods (q-bio.QM) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/1612.00667" title="Abstract" id="1612.00667"> arXiv:1612.00667 </a> [<a href="/pdf/1612.00667" title="Download PDF" id="pdf-1612.00667" aria-labelledby="pdf-1612.00667">pdf</a>, <a href="/format/1612.00667" title="Other formats" id="oth-1612.00667" aria-labelledby="oth-1612.00667">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Puch,+S">Santi Puch</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Aduriz,+A">Asier Aduriz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Casamitjana,+A">Adri脿 Casamitjana</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vilaplana,+V">Veronica Vilaplana</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Petrone,+P">Paula Petrone</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Operto,+G">Gr茅gory Operto</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cacciaglia,+R">Raffaele Cacciaglia</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Skouras,+S">Stavros Skouras</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Falcon,+C">Carles Falcon</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Molinuevo,+J+L">Jos茅 Luis Molinuevo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gispert,+J+D">Juan Domingo Gispert</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 4 pages + 1 page for acknowledgements and references. NIPS 2016 Workshop on Machine Learning for Health (NIPS ML4HC) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Neurons and Cognition (q-bio.NC); Applications (stat.AP) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/1612.00690" title="Abstract" id="1612.00690"> arXiv:1612.00690 </a> [<a href="/pdf/1612.00690" title="Download PDF" id="pdf-1612.00690" aria-labelledby="pdf-1612.00690">pdf</a>, <a href="/format/1612.00690" title="Other formats" id="oth-1612.00690" aria-labelledby="oth-1612.00690">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Eklund,+A">Anders Eklund</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lindquist,+M+A">Martin A. Lindquist</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Villani,+M">Mattias Villani</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> NeuroImage, Volume 155, 354-369 (2017) </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='item33'>[33]</a> <a href ="/abs/1612.00759" title="Abstract" id="1612.00759"> arXiv:1612.00759 </a> [<a href="/pdf/1612.00759" title="Download PDF" id="pdf-1612.00759" aria-labelledby="pdf-1612.00759">pdf</a>, <a href="/format/1612.00759" title="Other formats" id="oth-1612.00759" aria-labelledby="oth-1612.00759">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure </div> <div class='list-authors'><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=Duchesne,+T">Thierry Duchesne</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Computational Statistics & Data Analysis, 2018, 117, 154-161 </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/1612.00767" title="Abstract" id="1612.00767"> arXiv:1612.00767 </a> [<a href="/pdf/1612.00767" title="Download PDF" id="pdf-1612.00767" aria-labelledby="pdf-1612.00767">pdf</a>, <a href="/format/1612.00767" title="Other formats" id="oth-1612.00767" aria-labelledby="oth-1612.00767">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Asynchronous Stochastic Gradient MCMC with Elastic Coupling </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Springenberg,+J+T">Jost Tobias Springenberg</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Klein,+A">Aaron Klein</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Falkner,+S">Stefan Falkner</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hutter,+F">Frank Hutter</a></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='item35'>[35]</a> <a href ="/abs/1612.00775" title="Abstract" id="1612.00775"> arXiv:1612.00775 </a> [<a href="/pdf/1612.00775" title="Download PDF" id="pdf-1612.00775" aria-labelledby="pdf-1612.00775">pdf</a>, <a href="/format/1612.00775" title="Other formats" id="oth-1612.00775" aria-labelledby="oth-1612.00775">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A simple squared-error reformulation for ordinal classification </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Beckham,+C">Christopher Beckham</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pal,+C">Christopher Pal</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> v1: Camera-ready abstract for NIPS for Health Workshop (2016) v2: Clean-up of some sections, added appendix section where we briefly explore optimisation of quadratic weighted kappa (QWK) </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/1612.00778" title="Abstract" id="1612.00778"> arXiv:1612.00778 </a> [<a href="/pdf/1612.00778" title="Download PDF" id="pdf-1612.00778" aria-labelledby="pdf-1612.00778">pdf</a>, <a href="/format/1612.00778" title="Other formats" id="oth-1612.00778" aria-labelledby="oth-1612.00778">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Not Normal: the uncertainties of scientific measurements </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bailey,+D+C">David C. Bailey</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 17 pages, 5 figures. Auxiliary Excel file (<a href="http://UncertaintyDataDescription.xls" rel="external noopener nofollow" class="link-external link-http">this http URL</a>) lists sources of data </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Royal Society Open Science, 4, 160600 (2017) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Data Analysis, Statistics and Probability (physics.data-an) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/1612.00804" title="Abstract" id="1612.00804"> arXiv:1612.00804 </a> [<a href="/pdf/1612.00804" title="Download PDF" id="pdf-1612.00804" aria-labelledby="pdf-1612.00804">pdf</a>, <a href="/format/1612.00804" title="Other formats" id="oth-1612.00804" aria-labelledby="oth-1612.00804">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Restricted Strong Convexity Implies Weak Submodularity </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Elenberg,+E+R">Ethan R. Elenberg</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Khanna,+R">Rajiv Khanna</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dimakis,+A+G">Alexandros G. Dimakis</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Negahban,+S">Sahand Negahban</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Information Theory (cs.IT); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/1612.00824" title="Abstract" id="1612.00824"> arXiv:1612.00824 </a> [<a href="/pdf/1612.00824" title="Download PDF" id="pdf-1612.00824" aria-labelledby="pdf-1612.00824">pdf</a>, <a href="/format/1612.00824" title="Other formats" id="oth-1612.00824" aria-labelledby="oth-1612.00824">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning with Hierarchical Gaussian Kernels </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Steinwart,+I">Ingo Steinwart</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Thomann,+P">Philipp Thomann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Schmid,+N">Nico Schmid</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='item39'>[39]</a> <a href ="/abs/1612.00877" title="Abstract" id="1612.00877"> arXiv:1612.00877 </a> [<a href="/pdf/1612.00877" title="Download PDF" id="pdf-1612.00877" aria-labelledby="pdf-1612.00877">pdf</a>, <a href="/format/1612.00877" title="Other formats" id="oth-1612.00877" aria-labelledby="oth-1612.00877">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian sparse multiple regression for simultaneous rank reduction and variable selection </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chakraborty,+A">Antik Chakraborty</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=Mallick,+B+K">Bani K. Mallick</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/1612.00922" title="Abstract" id="1612.00922"> arXiv:1612.00922 </a> [<a href="/pdf/1612.00922" title="Download PDF" id="pdf-1612.00922" aria-labelledby="pdf-1612.00922">pdf</a>, <a href="/format/1612.00922" title="Other formats" id="oth-1612.00922" aria-labelledby="oth-1612.00922">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An efficient and doubly robust empirical likelihood approach for estimating equations with missing data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+T">Tianqing Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yuan,+X">Xiaohui Yuan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Z">Zhaohai Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+A">Aiyi Liu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 31 pages,0 figures,7 tables </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/1612.00939" title="Abstract" id="1612.00939"> arXiv:1612.00939 </a> [<a href="/pdf/1612.00939" title="Download PDF" id="pdf-1612.00939" aria-labelledby="pdf-1612.00939">pdf</a>, <a href="/format/1612.00939" title="Other formats" id="oth-1612.00939" aria-labelledby="oth-1612.00939">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Projection Sparse Principal Component Analysis: an efficient least squares method </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Merola,+G+M">Giovanni Maria Merola</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 31 pages, submitted for publication </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/1612.00951" title="Abstract" id="1612.00951"> arXiv:1612.00951 </a> [<a href="/pdf/1612.00951" title="Download PDF" id="pdf-1612.00951" aria-labelledby="pdf-1612.00951">pdf</a>, <a href="/format/1612.00951" title="Other formats" id="oth-1612.00951" aria-labelledby="oth-1612.00951">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Pitfalls of Nested Monte Carlo </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rainforth,+T">Tom Rainforth</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cornish,+R">Robert Cornish</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yang,+H">Hongseok Yang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wood,+F">Frank Wood</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Appearing in NIPS Workshop on Advances in Approximate Bayesian Inference 2016 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Methodology (stat.ME); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/1612.01014" title="Abstract" id="1612.01014"> arXiv:1612.01014 </a> [<a href="/pdf/1612.01014" title="Download PDF" id="pdf-1612.01014" aria-labelledby="pdf-1612.01014">pdf</a>, <a href="/format/1612.01014" title="Other formats" id="oth-1612.01014" aria-labelledby="oth-1612.01014">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions </div> <div class='list-authors'><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=Descoteaux,+M">Maxime Descoteaux</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">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/1612.01020" title="Abstract" id="1612.01020"> arXiv:1612.01020 </a> [<a href="/pdf/1612.01020" title="Download PDF" id="pdf-1612.01020" aria-labelledby="pdf-1612.01020">pdf</a>, <a href="/format/1612.01020" title="Other formats" id="oth-1612.01020" aria-labelledby="oth-1612.01020">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Hypothesis Transfer Learning via Transformation Functions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Du,+S+S">Simon Shaolei Du</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Koushik,+J">Jayanth Koushik</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Singh,+A">Aarti Singh</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Poczos,+B">Barnabas Poczos</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by NIPS 2017 </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/1612.01055" title="Abstract" id="1612.01055"> arXiv:1612.01055 </a> [<a href="/pdf/1612.01055" title="Download PDF" id="pdf-1612.01055" aria-labelledby="pdf-1612.01055">pdf</a>, <a href="/format/1612.01055" title="Other formats" id="oth-1612.01055" aria-labelledby="oth-1612.01055">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Modeling trajectories of mental health: challenges and opportunities </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Erdman,+L">Lauren Erdman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sharma,+E">Ekansh Sharma</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Unternahrer,+E">Eva Unternahrer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dass,+S+H">Shantala Hari Dass</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=ODonnell,+K">Kieran ODonnell</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mostafavi,+S">Sara Mostafavi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Edgar,+R">Rachel Edgar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kobor,+M">Michael Kobor</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gaudreau,+H">Helene Gaudreau</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Meaney,+M">Michael Meaney</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Goldenberg,+A">Anna Goldenberg</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> extended abstract for ML4HC at NIPS 2016, 4 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Applications (stat.AP) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/1612.01089" title="Abstract" id="1612.01089"> arXiv:1612.01089 </a> [<a href="/pdf/1612.01089" title="Download PDF" id="pdf-1612.01089" aria-labelledby="pdf-1612.01089">pdf</a>, <a href="/format/1612.01089" title="Other formats" id="oth-1612.01089" aria-labelledby="oth-1612.01089">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Novel Approach for Big Data Analytics in Future Grids Based on Free Probability </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ling,+Z">Zenan Ling</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Qiu,+R+C">Robert C. Qiu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=He,+X">Xing He</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lei,+C">Chu Lei</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 5 figures </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/1612.01095" title="Abstract" id="1612.01095"> arXiv:1612.01095 </a> [<a href="/pdf/1612.01095" title="Download PDF" id="pdf-1612.01095" aria-labelledby="pdf-1612.01095">pdf</a>, <a href="/format/1612.01095" title="Other formats" id="oth-1612.01095" aria-labelledby="oth-1612.01095">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Representing Independence Models with Elementary Triplets </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Pe%C3%B1a,+J+M">Jose M. Pe帽a</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1612.01158" title="Abstract" id="1612.01158"> arXiv:1612.01158 </a> [<a href="/pdf/1612.01158" title="Download PDF" id="pdf-1612.01158" aria-labelledby="pdf-1612.01158">pdf</a>, <a href="/format/1612.01158" title="Other formats" id="oth-1612.01158" aria-labelledby="oth-1612.01158">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Properties and Bayesian fitting of restricted Boltzmann machines </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kaplan,+A">Andee Kaplan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nordman,+D">Daniel Nordman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Vardeman,+S">Stephen Vardeman</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 20 pages, 13 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> <dt> <a name='item49'>[49]</a> <a href ="/abs/1612.01159" title="Abstract" id="1612.01159"> arXiv:1612.01159 </a> [<a href="/pdf/1612.01159" title="Download PDF" id="pdf-1612.01159" aria-labelledby="pdf-1612.01159">pdf</a>, <a href="/format/1612.01159" title="Other formats" id="oth-1612.01159" aria-labelledby="oth-1612.01159">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the instability and degeneracy of deep learning models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kaplan,+A">Andee Kaplan</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Nordman,+D">Daniel Nordman</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Vardeman,+S">Stephen Vardeman</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 28 pages, 1 figure </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='item50'>[50]</a> <a href ="/abs/1612.01200" title="Abstract" id="1612.01200"> arXiv:1612.01200 </a> [<a href="/pdf/1612.01200" title="Download PDF" id="pdf-1612.01200" aria-labelledby="pdf-1612.01200">pdf</a>, <a href="/format/1612.01200" title="Other formats" id="oth-1612.01200" aria-labelledby="oth-1612.01200">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Intra-day Activity Better Predicts Chronic Conditions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Quisel,+T">Tom Quisel</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kale,+D+C">David C. Kale</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Foschini,+L">Luca Foschini</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Presented at the NIPS 2016 Workshop on Machine Learning for Health </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 533 entries : <span>1-50</span> <a href=/list/stat/2016-12?skip=50&show=50>51-100</a> <a href=/list/stat/2016-12?skip=100&show=50>101-150</a> <a href=/list/stat/2016-12?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2016-12?skip=500&show=50>501-533</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2016-12?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2016-12?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2016-12?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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