Statistical and Algorithmic Foundations of Reinforcement Learning
Short course at Beijing International Center for Mathematical Research and School of Mathematical Science, Peking University, July 2023
Non-asymptotic Analysis for Reinforcement Learning (part 1) (part 2) (part 3)
ACM SIGMETRICS 2023, together with Yuxin Chen and Yuejie Chi
Reinforcement Learning: Fundamentals, Algorithms, and Theory
International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2022
ICSA Applied Statistics Symposium, Sep 2021
A Non-Asymptotic Framework for Approximate Message Passing Algorithm
Probability Seminar, UC Davis, Sep 2022
Applied Probability and Risk Seminar, Columbia University, Mar 2023
Statistics Seminar, University of Chicago, Mar 2023
Statistics Seminar, Stanford University, Apr 2023
Minimum L1-norm interpolators: Precise asymptotics and multiple descent
Harvard Probabilitas Seminar, Mar 2022
Statistics Seminar, Cambridge University, May 2022
Workshop on Seeking Low Dimensionality in Deep Neural Networks (SLowDNN), Nov 2021
Breaking the Sample Size Barrier in Reinforcement Learning
Statistics Seminar, Yale University, Jan 2021
Statistics Seminar, Wharton Statistics Seminar, University of Pennsylvania, Feb 2021
Statistics Seminar, Duke University, Sep 2021
Stochastics and Statistics Seminar, MIT, Oct 2021
Breaking the Sample Size Barrier in Statistical Inference and Reinforcement Learning
Wilks Statistics Seminar, ORFE, Princeton University, Dec 2020
Statistics Seminar, Rutgers University, Dec 2020
Reliable hypothesis testing paradigms in high dimensions
Young Data Science Researcher Seminar, ETH Zürich, Oct 2020
Statistics Seminar, Columbia University, Oct 2020
Statistics Seminar, Michigan State University, Oct 2020
The Lasso with general Gaussian designs and its applications
Joint Statistical Meetings, Aug 2020
Breaking the sample size barrier in model-based reinforcement learning
TBSI Workshop on Learning Theory, July 2020
INFORMS, Nov 2020
Understanding the distribution of the Lasso and its applications
STATML Group, Carnegie Mellon University, March 2020
Towards a better understanding of regularization in kernel learning
Statistics seminar, Cambridge University, 2018
Big Data and Computational Social Science Lecture, UBC, 2019
TBSI Workshop on Data Science, Shenzhen, December 2019
Geometric analysis of hypothesis testing and early stopping for boosting
Statistics seminar, University of Pennsylvania, 2018
Statistics seminar, University of Michigan, 2018
Statistics seminar, Stanford University, 2018
Statistics seminar, Carnegie Mellon University, 2018
Visiting researcher at Institute for Mathematical Research (FIM), ETH Zürich: Sep 2015 - Dec 2015
Visiting researcher at Department of Mathematics, City University of Hong Kong: Aug 2012 - Oct 2012 Mathematical Foundation of Immunology and Protein Structure, advised by Prof. Stephen Smale