JSM 2017 Online Program

Legend:
CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme

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304	Tue, 8/1/2017, 8:30 AM - 10:20 AM		CC-313
Statistical Learning: Dimension Reduction — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Vadim Zipunnikov, Johns Hopkins University
8:35 AM	Supervised Dimension Reduction with Application to Driver Gene Detection — Yichen Cheng
8:50 AM	Sparse Principal Component Analysis with Missing Observations — Seyoung Park ; Hongyu Zhao, Yale University
9:05 AM	On the Similarity of Principal Components, Random Projections and Random Column Subsampling for Dimension Reduction in High-Dimensional Linear Regression — Martin Slawski, George Mason Univ
9:20 AM	Information Tests on Statistical Submanifolds — Michael Trosset, Indiana University ; Carey E Priebe, Johns Hopkins University
9:35 AM	Dimension Selection for Two-Step Linear Discriminant Analysis — Ting-Li Chen, Institute of Statistical Sciences, Academia Sinica ; Yi-Heng Sun, National Taiwan University
9:50 AM	Regularized Discriminant Analysis in Presence of Cellwise Contamination — Stephanie Aerts, University of Liège ; Ines Wilms, KU Leuven
10:05 AM	Sequential Co-Sparse Factor Regression — Aditya Mishra, University of Connecticut ; Kun Chen, Department of Statistics, University of Connecticut ; Dipak K Dey, university of connecticut