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NCRG

CONVEX OPTIMIZATION

CONVEX OPTIMIZATION

 

This course builds the ability of recognizing and solving convex optimization problems that arise in applications.

Contents are as follow:

 


First, Convex sets, functions, and optimization problems.

Second, Basics of convex analysis.

Third, Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems.

Forth, Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods.

Last, Applications to signal processing, statistics and machine learning, control and mechanical engineering,
 digital and analog circuit design, and finance.


Textbook: Convex Optimization, Stephen Boyd and Lieven Vandenberghe

 

 

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