Spring 2023

Spring 2023

Feb 17 – Eric Vanden-Eijnden (New York University)
Generative Models, Normalizing Flows and Monte Carlo Samplers

Feb 24
– Andrej Risteski – (Carnegie Mellon University)
On the statistical cost of score matching

Mar 3 – Tim Kunisky (Yale University)
Spectral pseudorandomness and the clique number of the Paley graph

Mar 10 – Kuikui Liu (University of Washington)
Spectral Independence: A New Tool to Analyze Markov Chains

Mar 17 – Paromita Dubey (University of Southern California)
Geometric EDA for Random Objects

Mar 24 – Martin Wainwright (MIT)
Variational methods in reinforcement learning

Mar 31
– No Seminar

Apr 7
– Florian Gunsilius (University of Michigan)
Free Discontinuity Design (joint w/David van Dijcke)

Apr 14 – No Seminar

Apr 21 – Matias Cattaneo (Princeton University)
Adaptive Decision Tree Methods

Apr 28 – Samory Kpotufe (Columbia University)
Adaptivity in Domain Adaptation and Friends

May 5 – Vianney Perchet (Center for Research in Economics and Statistics, ENSAE Paris)
Learning learning-augmented algorithms.  The example of stochastics scheduling

May 12 – Jayadev Acharya (Cornell University)
Statistical Inference Under Information Constraints: User level approaches

MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307