| dc.contributor.author | Bertsekas, Dimitri | en_US |
| dc.coverage.temporal | Spring 2010 | en_US |
| dc.date.issued | 2010-06 | |
| dc.identifier | 6.253-Spring2010 | |
| dc.identifier | local: 6.253 | |
| dc.identifier | local: IMSCP-MD5-550c92c72eeeddda8f303c319e0c6fc4 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/76254 | |
| dc.description.abstract | This course will focus on fundamental subjects in (deterministic) optimization, connected through the themes of convexity, geometric multipliers, and duality. The aim is to develop the core analytical and computational 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 will be central, and will allow an intuitive, highly visual, geometrical approach to the subject. This theory will be developed in detail and in parallel with the optimization topics. The first part of the course develops the analytical issues of convexity and duality. The second part is devoted to convex optimization algorithms, and their applications to a variety of large-scale optimization problems from resource allocation, machine learning, engineering design, and other areas. | en_US |
| dc.language | en-US | en_US |
| dc.relation | | en_US |
| dc.rights.uri | Usage Restrictions: This site (c) Massachusetts Institute of Technology 2013. 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 | convexity | en_US |
| dc.subject | optimization | en_US |
| dc.subject | geometric duality | en_US |
| dc.subject | Lagrangian duality | en_US |
| dc.subject | Fenchel duality | en_US |
| dc.subject | cone programming | en_US |
| dc.subject | semidefinite programming | en_US |
| dc.subject | subgradients | en_US |
| dc.subject | constrained optimization | en_US |
| dc.subject | gradient projection | en_US |
| dc.title | 6.253 Convex Analysis and Optimization, Spring 2010 | en_US |
| dc.title.alternative | Convex Analysis and Optimization | en_US |
