6.253 Convex Analysis and Optimization, Spring 2004
Name
6-253-spring-2004/contents/index.htm
Size
15.7 KB
Format
HTML
Checksum (MD5)
219678922db4544b542395aeefdb1dd7
Author(s)
Bertsekas, Dimitri
Alternative Title
Convex Analysis and Optimization
Date Issued
June 2004
Abstract
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.
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
Lagrange multipliers
Fritz John optimality
Exact penalty functions
conjugate duality
conjugate functions
Fenchel duality
exact penalty functions
dual computational methods
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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