Courses of Study 2018-2019 
    Feb 02, 2023  
Courses of Study 2018-2019 [ARCHIVED CATALOG]

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ORIE 6326 - [Convex Optimization]

Spring. Next Offered: 2019-2020. 3 credits. Student option grading.


Convex optimization generalizes least-squares, linear and quadratic programming, and semidefinite programming, and forms the basis of many methods for non-convex optimization. This course focuses on recognizing and solving convex optimization problems that arise in applications, and introduces a few algorithms for convex optimization. Topics include: Convex sets, functions, and optimization problems.  Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Algorithms: interior-point, subgradient, proximal gradient, splitting methods such as ADMM. Applications to statistics and machine learning, signal processing, control and mechanical engineering, and finance.

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