{"id":6,"date":"2024-04-04T05:27:14","date_gmt":"2024-04-04T02:27:14","guid":{"rendered":"https:\/\/sisu.ut.ee\/tartumvs2020\/invited-speakers\/"},"modified":"2024-05-16T10:58:56","modified_gmt":"2024-05-16T07:58:56","slug":"invited-speakers","status":"publish","type":"page","link":"https:\/\/sisu.ut.ee\/tartumvs2020\/scientific-programme\/invited-speakers\/","title":{"rendered":"Invited speakers and sessions"},"content":{"rendered":"<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-align-left\"><strong><span style=\"color: #3366cc;\">Invited speakers<\/span><\/strong><\/h3>\n\n\n\n<p><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Adelchi Azzalini, University of Padova, Italy<br><em>On the use of ordered factors as explanatory variables<\/em><br><br><\/li>\n\n\n\n<li>Katarzyna Filipiak, Pozna\u0144 University of Technology, Poland<br><em>Safety belt estimation under the multivariate linear model<\/em><br><br><\/li>\n\n\n\n<li>Solomon W. Harrar, University of Kentucky, USA<br><em>Overcoming biomarker bias with finite mixtures for multivariate outcomes<\/em><br><br><\/li>\n\n\n\n<li>Thomas Mikosch, University of Copenhagen, Denmark<br><em>Extreme value theory for multivariate heavy-tailed time series<\/em><br><br><\/li>\n\n\n\n<li>Hannu Oja, University of Turku<br><em>Notions of dispersion, kurtosis and information: From principal components to independent components<\/em><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\">\u00a0<\/h4>\n\n\n\n<h4 class=\"wp-block-heading\">\u00a0<\/h4>\n\n\n\n<h3 class=\"wp-block-heading\"><strong><span style=\"color: #3366cc;\">Invited sessions<\/span><\/strong><\/h3>\n\n\n\n<h6 class=\"wp-block-heading\">\u00a0<\/h6>\n\n\n\n<h6 class=\"wp-block-heading\"><strong>New Analytics for Complex Correlated Data<\/strong><\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Organizer: Peter Song, University of Michigan, USA, <em>Quantile mediation analysis\u00a0<\/em><\/li>\n\n\n\n<li>Margaret Banker, Northwestern University, USA, <em>Changepoint and functional parameter estimation with an accelerometer data application<\/em><\/li>\n\n\n\n<li>Ostap Okhrin, Dresden University of Technology, Germany, <em>Addressing maximization bias in reinforcement learning with two-sample testing<\/em><\/li>\n\n\n\n<li>Menggang Yu, University of Michigan, USA, <em>Sufficient dimension reduction for populations with structured heterogeneity<\/em><\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-preformatted\"><\/pre>\n\n\n\n<h6 class=\"wp-block-heading\">\u00a0<\/h6>\n\n\n\n<h6 class=\"wp-block-heading\">\u00a0<\/h6>\n\n\n\n<h6 class=\"wp-block-heading\"><strong>Predictive Density Estimation<\/strong><\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Organizer: \u00c9ric Marchand, Universit\u00e9 de Sherbrooke, Canada, <em>The search for efficient predictive density estimators in multivariate models<\/em><\/li>\n\n\n\n<li>Takeru Matsuda, University of Tokyo, Japan, <em>Matrix estimation and prediction via singular value shrinkage<\/em><\/li>\n\n\n\n<li>Fumiyasu Komaki, University of Tokyo, Japan, <em>Improving predictions based on right invariant priors for group models<\/em><\/li>\n\n\n\n<li>Keisuke Yano, Institute of Statistical Mathematics, Japan, <em>Predictive inference in linear mixed models<\/em><\/li>\n<\/ul>\n\n\n\n<pre class=\"wp-block-preformatted\"><\/pre>\n\n\n\n<h6 class=\"wp-block-heading\">\u00a0<\/h6>\n\n\n\n<h6 class=\"wp-block-heading\">\u00a0<\/h6>\n\n\n\n<h6 class=\"wp-block-heading\"><strong>Statistical Modeling and Inference on Complex Network Data<\/strong><\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Organizer: Wen Zhou, Colorado State University, USA,\u00a0 <em>Detection and statistical inference on informative core and periphery structures in weighted directed networks<\/em><\/li>\n\n\n\n<li>Yuan Zhang, Ohio State University, USA,\u00a0 <em>U-statistic reduction: Higher-order accurate risk control and statistical-computational trade-off, with application to network method-of-moments<\/em><\/li>\n\n\n\n<li>Ji Zhu, University of Michigan, USA,<em> A latent space model for hypergraphs with diversity and heterogeneous popularity<\/em><\/li>\n\n\n\n<li>Yunpeng Zhao, Colorado State University, USA, <em>Community detection with heterogeneous block covariance mode<\/em><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Invited speakers \u00a0 \u00a0 Invited sessions \u00a0 New Analytics for Complex Correlated Data \u00a0 \u00a0 Predictive Density Estimation \u00a0 \u00a0 Statistical Modeling and Inference on Complex Network Data<\/p>\n","protected":false},"author":196,"featured_media":0,"parent":12,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-6","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/pages\/6","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/users\/196"}],"replies":[{"embeddable":true,"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/comments?post=6"}],"version-history":[{"count":15,"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/pages\/6\/revisions"}],"predecessor-version":[{"id":285,"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/pages\/6\/revisions\/285"}],"up":[{"embeddable":true,"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/pages\/12"}],"wp:attachment":[{"href":"https:\/\/sisu.ut.ee\/tartumvs2020\/wp-json\/wp\/v2\/media?parent=6"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}