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CC = Colorado Convention Center   H = Hyatt Regency Denver at Colorado Convention Center
* = applied session       ! = JSM meeting theme

Activity Details

136 Mon, 7/29/2019, 8:30 AM - 10:20 AM CC-701
Recent Advances in Dimension Reduction — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Linda Ng Boyle, University of Washington
8:35 AM Signal-Plus-Noise Matrix Models: Eigenvector Deviations and Fluctuations
Joshua Cape, Johns Hopkins University; Minh Tang, Johns Hopkins University; Carey E Priebe, Johns Hopkins University
8:50 AM Representative Approach for Big Data Dimension Reduction with Binary Responses
Xuelong Wang, University of Illinois at Chicago
9:05 AM A Sufficient Dimension Reduction Method via Expectation of Conditional Difference
Qingcong Yuan, Miami University; Wenhui Sheng, Marquette University; Xiangrong Yin, University of Kentucky
9:20 AM GMDR: Generalized Matrix Decomposition Regression
Yue Wang, Fred Hutchinson Cancer Center; Ali Shojaie, University of Washington; Timothy Randolph, Fred Hutchinson Cancer Research Center; Jing Ma, Fred Hutchinson Cancer Center
9:35 AM Matrix-Free Likelihood Methods for Exploratory Factor Analysis with High-Dimensional Gaussian Data
Fan Dai, Iowa State University; Somak Dutta, Iowa State University; Ranjan Maitra, Iowa State University
9:50 AM Principal Component-Guided Sparse Regression

Kenneth Tay, Stanford University; Jerome Friedman, Stanford University; Robert Tibshirani, Stanford University
10:05 AM High-Dimensional Prediction with Sparse Principal Components

Lei Ding, Indiana University Bloomington; Daniel McDonald, Indiana University Bloomington