Spring 2022 Course Descriptions
CS 168-01 Convex Optimization
(Cross-listed with EE 109) Convex optimization theory and algorithms. Convex sets, convex functions and convex optimization problems; duality theory and optimality conditions; algorithms for solving convex problems including descent, gradient descent, Newton and interior point methods. Examples of application taken from communications, signal processing and other fields. Project.
Prerequisite: Math 70 or graduate standing.