Carnegie Mellon University

Modern Convex Optimization

Course Number: 47851

This course will cover the main foundations of convex optimization. The goal is to develop solid command of the foundational blocks of this discipline at the highest possible level. The course topics will include a thorough treatment of duality, optimality conditions, conic optimization, and general algorithmic templates for first-order, second- and higher-order algorithms.

 

Degree: PhD
Concentration: Operations Research
Academic Year: 2022-2023
Semester(s): Mini 4
Required/Elective: Elective
Units: 6

Format

Lecture: 100min/wk and Recitation: 50min/wk

Textbook(s):

Books and research articles.

Learning Objectives

Recognize and be able to solve problems amenable to convex optimization techniques. Be well-versed on the use of convex duality.