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

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