Convex Optimization: Theory and Applications

This lecture covers the theory and applications of convex optimization, focusing on convex sets, convex functions, and the dual of a quadratically constrained quadratic program. It explains how to determine if a set is convex, the composition rule for convex functions, and the dual problem of a QCQP. The lecture also demonstrates the convexity of specific functions and provides insights into reformulating problems as second-order cone programs.