Spring 2021

Feb 19

 Jerry Li (Microsoft Research) – Faster and Simpler Algorithms for List Learning

Feb 26 

Yury Polyanskiy (MIT) – Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models

Mar 5

Bhaswar B. Bhattacharya (University of Pennsylvania – Wharton School) – Detection Thresholds for Distribution-Free Non-Parametric Tests: The Curious Case of Dimension 8

Mar 12

James Robins (Harvard) –On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning

Mar 19 

 Daniel Roy (University of Toronto) – Relaxing the I.I.D. Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization

Mar 26

Vladimir Vovk (Royal Holloway, University of London) – Testing the I.I.D. assumption online

Apr 2

Thibaut Le Gouic (MIT) – Sampler for the Wasserstein barycenter

Apr 9

Suriya Gunasekar (Microsoft Research) – Functions space view of linear multi- channel convolution networks with bounded weight norm

Apr 16

Eric Laber (Duke University) – Sample size considerations in precision medicine

Apr 23

Hilary Finucane (Broad Institute) – Prioritizing genes from genome-wide association studies

May 14

Ann Lee (Carnegie Mellon University) – Likelihood-Free Frequentist Inference