Convex Optimization. (3-0) 3 Credit Hours

Catalog description

Prerequisite: Graduate standing in engineering or consent of instructor. This course introduces the theory of convex optimization and provides practical tools to identify and solve related problems. Convex optimization has applications in diverse fields, including control systems, machine learning, supply networks, and robotics. This course covers foundational concepts, including convex sets and functions, modeling aspects, and practical results. Also, this course includes a review of convex analysis, least squares, linear and quadratic programs, optimality conditions, duality theory, interior-point methods, and convex relaxation. This course has Differential Tuition.