Lecture
This lecture covers algorithms for composite optimization, focusing on proximal operators, proximal gradient methods, and linear minimization oracles. It discusses the design of algorithms for finding solutions, including quadratic majorizers and geometric illustrations. The lecture also delves into proximal-point operators, tractable prox-operators, and solution methods for composite convex minimization. Examples and theoretical bounds are provided for proximal-gradient algorithms and fast proximal-gradient schemes, showcasing their convergence and practical performance.