Learning How Neural Systems Govern Behavior: Motor Control, Decision-making, and Epilepsy

A reinforcement learning algorithm for restless bandits

Fitting a putative manifold to noisy data

Information theoretic perspectives on learning algorithms

Non-convex optimization and multiuser information theory

Smoothed Analysis of Low Rank Solutions to Semidefinite Programs via Burer Monteiro Factorization

Theory for local optima of nonconvex high-dimensional M-estimators

Training Deep Models for better Generalization, Calibration, and Adaptation.