Spring 2021 Online Seminars

Date Presenter Title
Wednesday, January 20
Time: 12:10-1:10 pm
Lihua Lei – Stanford University Distribution-Free Assessment of Population Overlap in Observational Studies
Wednesday, January 27
Time: 12:10-1:10 pm
Yuxin Chen – Princeton University Taming Nonconvexity in Statistical and Reinforcement Learning
Wednesday, February 3
Time: 12:10-1:10 pm
Liza Levina – University of Michigan Hierarchical Community Detection by Recursive Partitioning
Wednesday, February 10
Time: 12:10-1:10 pm
Yuting Wei – Carnegie Mellon University Breaking the Sample Size Barrier in Reinforcement Learning
Friday, February 12
Time: 12:10-1:10 pm
Elizabeth Ogburn – Johns Hopkins University Disentangling Confounding and Nonsense Associations Due to Dependence
Wednesday, February 17
Time: 12:10-1:10 pm
Gesine Reinert – University of Oxford Stein’s Method for Exponential Random Graph Models and Kernelized Goodness of Fit
Wednesday, February 24
Time: 12:10-1:10 pm
Jacob Steinhardt – University of California, Berkeley The Science of Measurement in Machine Learning
Friday, February 26
Time: 12:10-1:10 pm
Veronika Rockova – University of Chicago Metropolis-Hastings via Classification
Wednesday, March 3
Time: 12:10-1:10 pm
Will Fithian – University of California, Berkeley Conditional Calibration for False Discovery Rate Control under Dependence
Wednesday, March 17
Time: 12:10-1:10 pm
Tian Zheng – Columbia University Artificial Perceptual Learning: Image Categorization with Weak Supervision
Wednesday, March 24
Time: 12:10-1:10 pm
Hamsa Bastani – University of Pennsylvania Deploying an Artificial Intelligence System for COVID-19 Testing at the Greek Border
Wednesday, March 31
Time: 12:10-1:10 pm
Stephen Bates – University of California, Berkeley Distribution-Free, Risk-Controlling Prediction Sets
Wednesday, April 7
Time: 12:10-1:10 pm
Mikhail Belkin – University of California, San Diego Two Mathematical Lessons of Deep Learning
Wednesday, April 14
Time: 12:10-1:10 pm
Larry Wasserman – Carnegie Mellon University Causal Inference in the Time of Covid-19
Joint Seminar with the Wharton
Applied Economics Workshop      

Wednesday, April 21
Time: 12:10-1:10 pm
Isaiah Andrews – Harvard University Inference on Winners
Joint Seminar with the
Penn CIS Department
Wednesday, April 28
Time: 12:10-1:10 pm
Emmanuel Candès – Stanford University Reliable Predictions? Counterfactual Predictions? Equitable Treatment? Some Recent Progress In Predictive Inference
Wednesday, May 5
Time: 12:10-1:10 pm
Murat Erdogdu – University of Toronto On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness

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