Legend: CC = Colorado Convention Center H = Hyatt Regency Denver at Colorado Convention Center
Activity Details
391 * !
Tue, 7/30/2019,
2:00 PM -
3:50 PM
CC-106
Leveraging Disparate Sources of Data and Machine Learning to Improve Causal Inference — Topic Contributed Papers
ENAR , Section on Statistical Learning and Data Science, Social Statistics Section
Organizer(s): Johann A Gagnon-Bartsch, University of Michigan; Jann Spiess, Postdoctoral Research, Microsoft Research
Chair(s): Johann A Gagnon-Bartsch, University of Michigan
2:05 PM
Transfer Learning for Estimating Causal Effects Using Neural Networks
Soeren Kuenzel ; Jasjeet Sekhon, UC Berkeley; Bradly Reinhold Stadie, UC Berkeley; Nikita Vemuri, UC Berkeley
2:25 PM
ReLOOP: Precise Unbiased Estimation in Randomized Experiments Using Observational Auxilliary Data
Adam Sales, University of Texas At Austin ; Johann A Gagnon-Bartsch, University of Michigan; Anthony Botelho, Worcester Polytechnic Institute; Neil T Heffernan, Worcester Polytechnic Institute; Edward Wu, University of Michigan; Luke Miratrix, Harvard University
2:45 PM
Machine Learning for Estimating Causal Effects from High-Dimensional Observational Data
Fredrik Johansson, MIT
3:05 PM
Bayesian Inference for Sample Surveys in the Presence of High-Dimensional Auxiliary Information
Yutao Liu, Columbia University ; Andrew Gelman, Columbia University; Qixuan Chen, Columbia University
3:25 PM
Manipulation Proof Machine Learning
Daniel Bjorkegren, Brown University ; Joshua Blumenstock, University of California Berkeley
3:45 PM
Floor Discussion
