Winter 2021 STAT 31015

Course: STAT 31015=TTIC 31070, BUSN 36903, CAAM 31015, CMSC 35470

Title: Mathematical Computation IIA: Convex Optimization

Instructor(s): Mihai Anitescu

Teaching Assistant(s): TBA

Class Schedule: Sec 1: MW 4:10 PM–5:30 PM (Remote)

Office Hours: 

Textbook(s): Boyd, Convex Optimization

Description: This course covers the fundamentals of convex optimization. Topics will include basic convex geometry and convex analysis, KKT condition, Fenchel and Lagrange duality theory; six standard convex optimization problems and their properties and applications: linear programming, geometric programming, second-order cone programming, semidefinite programming, linearly and quadratically constrained quadratic programming. In the last part of the course we will examine the generalized moment problem --- a powerful technique that allows one to encode a wide variety of problems (in probability, statistics, control theory, financial mathematics, signal processing, etc) and solve them or their relaxations as convex optimization problems.

Prerequisite(s): STAT 30900/CMSC 37810