Fall 2019

Sep 6 Tengyuan Liang (University of Chicago)
GANs, Optimal Transport, and Implicit Density Estimation
E18-304
Sep 20 Samory Kpotufe (Columbia)
Some New Insights On Transfer Learning
E18-304
Sep 27 Adam Klivans (UT Austin)
Frontiers of Efficient Neural-Network Learnability
E18-304
Oct 11 Christopher Moore (Santa Fe Institute)
The Planted Matching Problem
E18-304
Oct 18 Stanislav Minsker (USC)
Towards Robust Statistical Learning Theory
E18-304
Oct 25 Maria-Pia Victoria-Feser (University of Geneva)
Accurate Simulation-Based Parametric Inference in High Dimensional Settings
E18-304
Nov 8 Yudong Chen (Cornell)
SDP Relaxation for Learning Discrete Structures: Optimal Rates, Hidden Integrality, and Semirandom Robustness
E18-304
Nov 15 Lenka Zdeborova (Institut de Physique Théorique, CNRS)
Understanding Machine Learning with Statistical Physics
E18-304
Nov 22 Tamara Broderick (MIT)
Automated Data Summarization for Scalability in Bayesian Inference
E18-304
Dec 6 Simon Tavaré (Columbia)
Inferring the Evolutionary History of Tumors
E18-304

Spring 2019

Feb 1 Andrea Montanari (Stanford)
Optimization of the Sherrington-Kirkpatrick Hamiltonian
32-141
Feb 8 Polina Golland (MIT CSAIL)
Medical Image Imputation
E18-304
Feb 15 Zhou Fan (Yale)
TAP free energy, spin glasses, and variational inference
E18-304
Feb 22 Nike Sun (MIT)
Capacity lower bound for the Ising perceptron
E18-304
Mar 1 Eric Kolaczyk (Boston University)
Why Aren’t Network Statistics Accompanied By Uncertainty Statements?
E18-304
Mar 8 Aditya Guntuboyina (UC Berkeley)
Univariate total variation denoising, trend filtering and multivariate Hardy-Krause variation denoising
E18-304
Mar 15 Alex Belloni (Duke University)
Subvector Inference in Partially Identified Models with Many Moment Inequalities
E18-304
Mar 22 Eliran Subag (New York University)
Optimization of random polynomials on the sphere in the full-RSB regime
E18-304
Apr 12 Aaditya Ramdas (Carnegie Mellon University)
Exponential line-crossing inequalities
E18-304
Apr 19 Dylan Foster (MIT)
Logistic Regression: The Importance of Being Improper
E18-304
Apr 26 Chao Gao (University of Chicago)
Robust Estimation: Optimal Rates, Computation and Adaptation
E18-304
May 3 Tracy Ke (Harvard)
Optimal Adaptivity of Signed-Polygon Statistics for Network Testing (Tracy Ke, Harvard University)
E18-304
May 10 Will Perkins (University of Illinois at Chicago)
Counting and sampling at low temperatures
E18-304