Courses
Spring 2024
IDS.160/9.521/18.656/6.S988: Mathematical Statistics: A Non-Asymptotic Approach
MIT, IDSS/BCS/MATH/EECS
Spring 2023
IDS.160/9.521/18.656: Mathematical Statistics: A Non-Asymptotic Approach
MIT, IDSS/BCS/MATH
Spring 2022
IDS.160/9.521/18.656: Mathematical Statistics: A Non-Asymptotic Approach
MIT, IDSS/BCS/MATH
Spring 2021
IDS.160/9.521/18.656: Mathematical Statistics: A Non-Asymptotic Approach
MIT, IDSS/BCS/MATH
Spring 2020
IDS.160/9.521/18.S998: Mathematical Statistics: A Non-Asymptotic Approach
MIT, IDSS/BCS/MATH
Fall 2019
9.520/6.860: Statistical Learning Theory and Applications
MIT, BCS/EECS
Fall 2018
9.520/6.860: Statistical Learning Theory and Applications
MIT, BCS/EECS
Winter 2018
STAT 405/705: Statistical Computing with R
University of Pennsylvania, Department of Statistics
Spring 2017
STAT 991: Online Methods in Machine Learning: Theory and Applications
University of Pennsylvania, Department of Statistics
Spring 2015
STAT 991: Concentration Inequalities and Applications
University of Pennsylvania, Department of Statistics
Fall 2009-2015
STAT 101: Intro to Statistics
University of Pennsylvania, Department of Statistics
Spring 2012, 2014
Statistical Learning Theory and Sequential Prediction
University of Pennsylvania, Department of Statistics
Summer 2012
Introduction to Statistical Learning Theory
The 21st Machine Learning Summer School (Kyoto, Japan)
Spring 2012
From Statistical Learning to Sequential Prediction: A Minimax Approach (minicourse)
ENSAE, Paris Graduate School of Economics, Statistics and Finance
Spring 2009
STAT 991: Regularization Methods
University of Pennsylvania, Department of Statistics