- Course
- CAAM 31015=STAT 31015, TTIC 31070, BUSN 36903, CMSC 35470
- Title
- Mathematical Computation IIA: Convex Optimization
- Instructor(s)
- Mihai Anitescu
- Teaching Assistant(s)
- TBA
- Class Schedule
- Sec 01: MW 3:00 PM–4:20 PM in Saieh 203
- Textbook(s)
- Boyd,
*Boyd, Convex Optimization* - Prerequisite(s)
- STAT 30900/CMSC 37810
- 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.