6.253 Convex Analysis and Optimization, Spring 2004

6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an in...

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Bibliographic Details
Main Author:	Bertsekas, Dimitri
Other Authors:	Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format:	Learning Object
Language:	en-US
Published:	2004
Subjects:	affine hulls recession cones global minima local minima optimal solutions hyper planes minimax theory polyhedral convexity polyhedral cones polyhedral sets convex analysis optimization convexity Lagrange multipliers duality continuous optimization saddle point theory linear algebra real analysis convex sets convex functions extreme points subgradients constrained optimization directional derivatives subdifferentials conical approximations Fritz John optimality Exact penalty functions conjugate duality conjugate functions Fenchel duality exact penalty functions dual computational methods
Online Access:	http://hdl.handle.net/1721.1/70523

Description
Summary:	6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject.

6.253 Convex Analysis and Optimization, Spring 2004

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