Explores convex functions, including checking convexity, transformations, examples, minimization, geometric intuition, Schur's Lemma, distance function, perspective function, and relative entropy.
Introduces convex optimization, focusing on the importance of convexity in algorithms and optimization problems.
Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.
Introduces convex sets and functions, discussing minimizers, optimality conditions, and characterizations, along with examples and key inequalities.
