517
Wed, 7/31/2019,
10:30 AM -
12:20 PM
CC-701
Deep Learning: Advances and Applications — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Devin Francom, Los Alamos
10:35 AM
Reinforcement Learning as a Solution to Systematic Social Bias in Deep Learning
Kathleen Gatliffe, University of Colorado Denver ; Audrey E Hendricks, University of Colorado Denver
10:50 AM
Deep Model-X Knockoff Generator Through Latent Variables
Ying Liu, Medical College of Wisconsin ; Cheng Zheng, University of Wisconsin at Milwakee
11:05 AM
Online Batch Decision Making with High-Dimensional Covariates
Chi-Hua Wang, Purdue University ; Guang Cheng, Purdue Statistics
11:20 AM
Uncertainty-Aware Black-Box Predictors with Coverage Guarantees
Jean Feng, University of Washington ; Arjun Sondhi, University of Washington; Jessica Perry, University of Washington; Noah Simon, University of Washington
11:35 AM
Signed Graph Neural Network
Mohammadreza Armandpour, Texas A&M University ; Debdeep Pati, Texas A&M University
11:50 AM
A Two-Stage Approach to Evaluate Predictive Accuracy of Deep Neural Networks
Georgianna Campbell, Naval Information Warfare Center Atlantic ; Emily Nystrom, Naval Information Warfare Center Atlantic; Hunter R. Lake, Naval Information Warfare Center Atlantic
12:05 PM
Semi-Supervised Sequence Learning Using Deep Generative Models with Applications to Healthcare Data
Weijing Tang, University of Michigan ; Ji Zhu, University of Michigan
