Online Program Home
  My Program

All Times EDT

Legend:
* = applied session       ! = JSM meeting theme

Activity Details

496 ! Thu, 8/6/2020, 10:00 AM - 2:00 PM Virtual
Dimension Reduction — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Aramayis Dallakyan, Texas A&M University
Bayesian Model Averaging Sufficient Dimension Reduction
Michael Declan Power, Temple University; Yuexiao Dong, Temple University
Principal Curve Approaches for Inferring 3D Chromatin Architecture
Elena Tuzhilina, Stanford University, Department of Statistics ; Trevor Hastie, Stanford University, Department of Statistics ; Mark Segal, UCSF, Department of Epidemiology and Biostatistics
On Sufficient Dimension Reduction via Principal Asymmetric Least Squares
Abdul-Nasah Soale, Temple University; Yuexiao Dong, Temple University
Learning Hierarchical Structures in Latent Attribute Models
Chenchen Ma, University of Michigan; Gongjun Xu, University of Michigan
A Supervised Framework for Linear Dimension Reduction Induced by Hypothesis Testing
Kisung You, University of Notre Dame; Lizhen Lin, University of Notre Dame
Canonical Correlation Analysis and Fusion Methods on a Large Face Database for Computer Vision
Cuixian Chen, University of North Carolina, Wilmington; Jasmine Gaston, University of North Carolina Wilmington; Summerlin Thompson, University of North Carolina Wilmington; Suhaela Eledkawi, Wright State University; Caroline Werther, University of North Carolina Wilmington; Yaw Chang, University of North Carolina Wilmington; Yishi Wang, University of North Carolina Wilmington; Guodong Guo, West Virginia University