Seminars

Seminars

Fall 2019

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

Spring 2019

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