Teaching
I served as a TA for several courses at UC Davis. Links point to course notes I prepared.
- STA 243 — Computational Statistics (Graduate) Spring 2023, 2022, 2020
- STA 142A — Statistical Learning Winter 2023, 2022, 2021, 2020
- STA 141C — Big-data and Statistical Computing Spring 2021
- STA 141A — Statistical Data Science Fall 2019, 2021
- STA 103 — Applied Statistics Winter 2019
- STA 013 — Elementary Statistics Fall 2018, Spring 2019
Reading List
Convex Optimization
- Lectures on Convex Optimization — Yurii Nesterov
- Convex Optimization: Algorithms and Complexity — Sébastien Bubeck
Reinforcement Learning
- Reinforcement Learning: An Introduction — Sutton & Barto
- Reinforcement Learning: Theory and Algorithms — Agarwal, Jiang, Kakade & Sun
Bandits
- Introduction to Multi-Armed Bandits — Aleksandrs Slivkins
- Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems — Bubeck & Cesa-Bianchi
High-dimensional Statistics
- High-Dimensional Probability — Roman Vershynin
Learning Theory
- Understanding Machine Learning: From Theory to Algorithms — Shalev-Shwartz & Ben-David
Courses & Blogs
- ELE522: Large-Scale Optimization for Data Science — Yuxin Chen, Princeton
- CS 6789: Foundations of Reinforcement Learning — Wen Sun & Sham Kakade, Cornell/UW
- Off the Convex Path — Blog on optimization & deep learning theory
