Introduction to Proximal Operators

This lecture covers the introduction to proximal operators and conditional gradient methods in the context of composite convex minimization problems. It discusses the mathematics behind data optimization, focusing on sparse regression, inverse covariance estimation, and graphical model selection. The lecture explores the theoretical foundations and practical applications of proximal-gradient algorithms, emphasizing computational efficiency and convergence guarantees.