Convex Optimization

4 credits

Basics of convex analysis: Convex sets, functions, and optimization problems. Optimization theory: Least-squares, linear, quadratic, geometric and semidefinite programming. Convex modeling. Duality theory. Optimality and KKT conditions. Applications in signal processing, statistics, machine learning, control communications, and design of engineering systems. Prerequisite: A A 510, CHEM E 510, E E 510, or M E 510. Offered: jointly with A A 578/CSE 578/M E 578.