Resources
Courses/Books
Robust Statistics, by Jacob Steinhardt (UC Berkeley)
A Modern Introduction to Online Learning, by Francesco Orabona (Boston University)
Bandit Algorithms, by Tor Lattimore (Deepmind) and Csaba Szepesvari (Deepmind, University of Alberta)
User-friendly introduction to PAC-Bayes bounds, by Pierre Alquier (RIKEN)
Introduction to Online Optimization/Learning, by Haipeng Luo (USC)
High-Dimensional Statistics: A Non-Asymptotic Viewpoint, by Martin J. Wainwright (UC Berkeley)
Stats 300B: Theory of Statistics II, by John Duchi (Stanford)
Harvard CS 229br: Advanced Topics in the theory of machine learning, by Boaz Barak (Harvard)
Learning Theory and Statistical Optimization repos, by Patrick Rebeschini (Oxford)
Algorithmic Foundations of Learning, by Patrick Rebeschini (Oxford)