EE194 – Convex Optimization

Spring 2017 – Professor Mai Vu

This course focuses on convex optimization theory and algorithms. Topics include convex sets, convex functions and convex optimization problems; duality theory and optimality conditions; algorithms for solving convex problems including descend, Newton and interior point methods. Examples of application are taken from communications, signal processing and other fields. Students will do a project as part of the course credit.

Optimization is widely used in engineering and scientific computing applications. This course is intended for students, researchers, and practitioners who want to use optimization tools in designing and optimizing an algorithm or system, and anyone interested in optimization. We aim to provide a balance between theory and algorithms, so that students can recognize and formulate a convex problem, understand and analyze the optimality conditions, and at the same time are able to write codes to find the optimal solutions.

Lectures: MW 3:00 – 4:15 PM, Halligan 111B

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