Mar 29, 2024  
2020-2021 Graduate Catalog 
    
2020-2021 Graduate Catalog [ARCHIVED CATALOG]

ELEG 601 - Convex Optimization

Credit(s): 3


CONVEX OPTIMIZATION
Component: Lecture
This course provides a comprehensive coverage of both the theoretical foundation and numerical algorithms for convex optimization. The main objectives of this course are to give students the tools and training to recognize convex optimization problems that arise in applications, and to present the basic theory of such problems as well as how to solve them numerically.

Topics covered in this course include: Convex sets, functions, and optimization problems; Basics of convex analysis; Least-squares, linear and quadratic programs, semidefinite programming, minimax; Optimality conditions, duality theory, theorems of alternative; Descent methods, Newton’s method, interior-point method; Applications.
Repeatable for Credit: N Allowed Units: 3 Multiple Term Enrollment: N Grading Basis: Student Option
RESTRICTIONS: Knowledge on linear algebra (e.g. MATH 351) and probability theory (e.g. ELEG 310); mathematical maturity in general.


Course Typically Offered: Fall