Fall 2023

Fall 2023

Sep 8 – Alex Wein (University of California, Davis)
Fine-Grained Extensions of the Low-Degree Testing Framework

Sep 15 – Vasilis Syrgkanis (Stanford University)
Source Condition Double Robust Inference on Functionals of Inverse Problems

Sep 29
– Vladimir Spokoinyi (Humboldt University of Berlin)
Estimation and Inference for Error-in-Operator Model

Oct 6 – Nikita Zhivotovskiy (University of California, Berkeley)
Sharper Risk Bounds for Statistical Aggregation

Oct 13 – Emmanuel Abbé (EPFL)
A Proof of the RM Code Capacity Conjecture

Oct 20 – Sam Hopkins (MIT)
The Full Landscape of Robust Mean Testing: Sharp Separations between Oblivious and Adaptive Contamination

Oct 27
– Stephen Bates (MIT)
Hypothesis Testing with Information Asymmetry

Nov 3
– Anna Gilbert (Yale University)
Project and Forget: Solving Large-Scale Metric Constrained Problems

Nov 17 – Jianfeng Lu (Duke University
Analysis of Flow-based Generative Models

Dec 1 – Lester Mackey (Microsoft Research)
Advances in Distribution Compression

Dec 8 – Nicolas Flammarion (EPFL)
Saddle-to-saddle Dynamics in Diagonal Linear Networks

Dec 15 – Zaid Harchaoui (University of Washington)
The Discrete Schrödinger Bridge, and the Ensuing Chaos


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