\n12:50<\/td>\n | Adjourn<\/td>\n | <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Thursday, July 30, 2020<\/strong> \n<\/strong>Virtual – U.S. New York\/Eastern Daylight Time<\/em><\/p>\n\n\n\nTime<\/th>\n | Description<\/th>\n | Speaker<\/th>\n | Slides<\/th>\n | Videos<\/th>\n<\/tr>\n<\/thead>\n | \n\n8:00-8:50<\/td>\n | Test Audio\/Visual<\/td>\n | Join the “Click Here to Test Audio\/Video Connections” session by navigating to the “Agenda” tab in Whova. (Note: we will not be able to assist with audio\/visual issues once the meeting has begun)<\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n9:00-10:15<\/td>\n | Parallel Sessions<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 Statistical Learning<\/td>\n | Org:\u00a0 Kohei Adachi<\/strong>, Osaka University \nKohei Adachi, <\/strong>Osaka University, Japan \nPrincipal Component versus Factor Analyses with their Intermediate Procedure in Matrix Decomposition Formulation<\/em><\/p>\nInge Koch<\/strong>, University of Western Australia \nPrincipal Components for High-Dimensional and Directional Data<\/em><\/p>\nGiuseppe Vinci<\/strong>, Rice University \nGraph Quilting: Graphical Model Selection from Partially Observed Covariances<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | Data Science<\/td>\n | Org:\u00a0 John Nardini<\/strong>, SAMSI \nJohn Nardini<\/strong>, SAMSI \nLearning Differential Equation Models for Noisy Biological Data<\/em><\/p>\nGlen Wright Colopy<\/strong>. Cenduit \nPersonalized Inference Protects Patients and Science<\/em><\/p>\nXinyi Li<\/strong>, SAMSI \nSparse Learning and Structure Identification for Ultra-High-Dimensional Image-on-Scalar Regression<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n10:15-10:25<\/td>\n | Break<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n10:25-11:15<\/td>\n | Plenary Talk<\/td>\n | Chair: Patrick Groenen<\/strong>, Erasmus University<\/p>\n David Dunson<\/strong>, Duke University \nGeneralized Bayes for Probabilistic Uncertainty Quantification in Unsupervised Learning<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n11:15-11:25<\/td>\n | Break<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n11:25-12:40<\/td>\n | Parallel Sessions<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 Statistical Computing<\/td>\n | Org:\u00a0 Richard Samworth<\/strong>, University of Cambridge \nHao Chen<\/strong>, University of California, Davis \nChange-point Analysis for Modern Data<\/em><\/p>\nYining Chen<\/strong>, London School of Economics \nJump or Kink: Super-efficiency in Segmented Linear Regression Break-point Estimation<\/em><\/p>\nTengyao Wang<\/strong>, University College London \nHigh-Dimensional, Multiscale Online Changepoint Detection<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 Data Science Technology<\/td>\n | Org: Jim Harner<\/strong>, West Virginia University \nJavier Luraschi<\/strong>, RStudio \nTraining ImageNet Using TensorFow and R<\/em><\/p>\nSoren Harner<\/strong>, LayerJot & Jim Harner<\/strong>, West Virginia University \nHarnessing Big Data and Machine Learning with Arrow Data Frames in R and Python<\/em><\/p>\nShih-Hsiung Chou<\/strong> & Phil Turk<\/strong>, Atrium Health \nCURVE: a Web Application for In-Hospital Resource Forecasting During the COVID-19 Outbreak<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 New Ideas for Old Problems<\/td>\n | Org: Deborshee Sen<\/strong>, SAMSI \nPulong Ma<\/strong>, SAMSI \nMultifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge<\/em><\/p>\nKate Moore<\/strong>, Wake Forest University<\/span> \nCommunities in Data<\/em><\/span><\/p>\nWenjia Wang<\/strong>, SAMSI<\/span> \nUncertainty Quantification for Bayesian Optimization<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n12:40<\/td>\n | Poster Session<\/td>\n | <\/td>\n<\/tr>\n | \n1:10<\/td>\n | Adjourn<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Friday, July 31, 2020<\/strong> \n<\/strong>Virtual – U.S. New York\/Eastern Daylight Time<\/em><\/p>\n\n\n\nTime<\/th>\n | Description<\/th>\n | Speaker<\/th>\n | Slides<\/th>\n | Videos<\/th>\n<\/tr>\n<\/thead>\n | \n\n8:00-8:50<\/td>\n | Test Audio\/Visual<\/td>\n | Join the “Click Here to Test Audio\/Video Connections” session by navigating to the “Agenda” tab in Whova. (Note: we will not be able to assist with audio\/visual issues once the meeting has begun)<\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n9:00-9:50<\/td>\n | Plenary Talk<\/td>\n | Chair: Peter Filzmoser<\/strong>, TU Wien<\/p>\n Robert Gramacy<\/strong>, Virginia Polytechnic \nReplication\u00a0or\u00a0Exploration? Sequential Design for Stochastic Simulation Experiments<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n9:50-10:00<\/td>\n | Break<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n10:00-11:15<\/td>\n | Parallel Sessions<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 JDSSV<\/td>\n | Orgs: Patrick Groenen<\/strong>, Erasmus University & Stefan Van Aelst<\/strong>, KU Leuven \nAndreas Alfons<\/strong>, Erasmus University \nCellwise and Rowwise Robust Regression with Compositional Covariates<\/em><\/p>\nEun-Kyung Lee<\/strong>, Ewha Woman’s University<\/span> \nTree-structured Models using Projection Pursuit Method and their Explanation<\/em><\/p>\nMu Zhu<\/strong>, University of Waterloo \nSome Statistical Applications of Generative Neural Networks \n<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n<\/td>\n | \u00a0 SAS<\/td>\n | Orgs:\u00a0 Brett Wujek<\/strong>, SAS Institute \nXan Gregg<\/strong>, SAS Institute \nUnderstanding Smoothers through Interactive Examples<\/em><\/p>\nKelci Miclaus<\/strong>, JMP Lifesciences \nThe Role of Visualization in Translational and Clinical Research<\/em><\/p>\nGuohui Wu<\/strong>, SAS Institute \nLocation matters: Estimating Spatial Regression Models with Large Spatial Weights Matrices using SAS Econometrics<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n11:15-11:25<\/td>\n | Break<\/td>\n | <\/td>\n | <\/td>\n | <\/td>\n<\/tr>\n | \n11:25-12:15<\/td>\n | Plenary Talk<\/td>\n | Chair:\u00a0David Banks<\/strong>, Duke University and SAMSI<\/p>\n Ming Yuan<\/strong>, Columbia University \nInformation Based Complexity of High Dimensional Sparse Functions<\/em><\/td>\n<\/td>\n | <\/td>\n<\/tr>\n | \n12:15-12:25<\/td>\n | Closing<\/td>\n | <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":" Due to COVID-19 this conference will be presented virtually July 29-31, 2020.\u00a0\u00a0 Registration is now closed By registering for this conference you (1) consent to the use of your personal information for the purpose of processing this registration, (2) agree that the conference may include your name, affiliation, and country of residence on the list […]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":998,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338"}],"collection":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/comments?post=15338"}],"version-history":[{"count":144,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338\/revisions"}],"predecessor-version":[{"id":16573,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/15338\/revisions\/16573"}],"up":[{"embeddable":true,"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/pages\/998"}],"wp:attachment":[{"href":"https:\/\/www.samsi.info\/wp-json\/wp\/v2\/media?parent=15338"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} | | | | | | | | | | | | |