Talks

The Surprising Power of Little Data

• Statistics Colloquium, Department of Statistics, The University of Chicago, Jan 2021
• MSR Seminar, Microsoft Research, Feb 2021
• Machine Learning Seminar, School of Computer Science, University of Waterloo, March 2021
• CS Colloquium, Computer Science Department, University of Arizona, Nov 2018

Meta-Learning for Mixed Linear Regression

• Theory Lunch, University of Washington, Feb 2020
• ICML'20, Virtual, June 2020
• Northwestern Junior Theorists Workshop 2020, Dec 2020
• NeurIPS'20, Virtual, Dec 2020
• The 2020 Junior Theorists Workshop at Northwestern CS: Meta-Learning for Mixed Linear Regression [Video]

Optimal Policy Value Estimation in Contextual Bandits

• AISTATS'20, Virtual, June 2020
• Google Bandits Seminar, Virtual, June 2021

Learning Populations of Parameters

• Theory Lunch, Stanford, April 2019
• ITA'19, San Diego, Feb 2019

Efficient Algorithms and Lower Bounds for Robust Linear Regression

• ML Lunch, Stanford, Jan 2019
• SODA '19, Jan 2019
• Workshop on Computational Efficiency and High-Dimensional Robust Statistics, TTI-Chicago, Aug 2018

Estimating Learnability in the Sublinear Data Regime

• Foundations of Data Science, Simons Institute, Nov 2018
• TOCA-SV, Google Mountain View, Nov 2018
• ML Seminar, University of Washington, July 2018
• Stanford ML Lunch, April 2018

Estimating the Covariance Spectrum

• Nanjing University, Sep 2017
• Microsoft Research Asia, Beijing, Aug 2017
• University of Southern California, July 2017
• TOCA-SV, May 2017
• Warton Seminars, UPenn Warton, April 2017
• IDeAS Seminar, Princeton University, April 2017
• China Theory Week, Chinese University of Hong Kong, Aug 2016
• ML Lunch, Stanford, Jan 2016
• Theory Lunch, Stanford, Dec 2015

Approximating the Spectrum of a Graph

• KDD'18, London, Aug 2018

Recovering Structured Probability Matrices

• ITCS'18, Boston, Jan 2018
• Theory Lunch, Stanford, Feb 2017