dc.contributor.author | Bertsekas, Dimitri | en_US |
dc.coverage.temporal | Spring 2004 | en_US |
dc.date.issued | 2004-06 | |
dc.identifier | 6.253-Spring2004 | |
dc.identifier | local: 6.253 | |
dc.identifier | local: IMSCP-MD5-69ba2e33bd2e74035f531c2e1380f111 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/70523 | |
dc.description.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. | en_US |
dc.language | en-US | en_US |
dc.rights.uri | Usage Restrictions: This site (c) Massachusetts Institute of Technology 2012. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. | en_US |
dc.subject | affine hulls | en_US |
dc.subject | recession cones | en_US |
dc.subject | global minima | en_US |
dc.subject | local minima | en_US |
dc.subject | optimal solutions | en_US |
dc.subject | hyper planes | en_US |
dc.subject | minimax theory | en_US |
dc.subject | polyhedral convexity | en_US |
dc.subject | polyhedral cones | en_US |
dc.subject | polyhedral sets | en_US |
dc.subject | convex analysis | en_US |
dc.subject | optimization | en_US |
dc.subject | convexity | en_US |
dc.subject | Lagrange multipliers | en_US |
dc.subject | duality | en_US |
dc.subject | continuous optimization | en_US |
dc.subject | saddle point theory | en_US |
dc.subject | linear algebra | en_US |
dc.subject | real analysis | en_US |
dc.subject | convex sets | en_US |
dc.subject | convex functions | en_US |
dc.subject | extreme points | en_US |
dc.subject | subgradients | en_US |
dc.subject | constrained optimization | en_US |
dc.subject | directional derivatives | en_US |
dc.subject | subdifferentials | en_US |
dc.subject | conical approximations | en_US |
dc.subject | Lagrange multipliers | en_US |
dc.subject | Fritz John optimality | en_US |
dc.subject | Exact penalty functions | en_US |
dc.subject | conjugate duality | en_US |
dc.subject | conjugate functions | en_US |
dc.subject | Fenchel duality | en_US |
dc.subject | exact penalty functions | en_US |
dc.subject | dual computational methods | en_US |
dc.title | 6.253 Convex Analysis and Optimization, Spring 2004 | en_US |
dc.title.alternative | Convex Analysis and Optimization | en_US |