Legend:
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