|
|
|
|
| LEADER |
02475nam a22002297a 4500 |
| 001 |
710865 |
| 008 |
150421t20152015xxe ||| |||| 00| 0 eng d |
| 009 |
PPN185102441 |
| 020 |
|
|
|a 9781886529281 (rel.)
|
| 020 |
|
|
|a 1886529280
|
| 041 |
0 |
|
|a eng
|
| 100 |
1 |
|
|a Bertsekas, Dimitri P.,
|d 1942-
|
| 245 |
1 |
0 |
|a Convex optimization algorithms
|c Dimitri P. Bertsekas.
|
| 260 |
|
|
|a Nashua (N.H.) :
|b Athena Scientific.
|
| 260 |
|
|
|c C 2015.
|
| 300 |
|
|
|a 1 vol. (XII-564 p.) :
|b illustrations ;
|c 25 cm.
|
| 504 |
|
|
|a Réf. bibliographiques p. 519-556. Index
|
| 505 |
0 |
|
|a 1. Convex optimization models : an overview -- 1.1 Lagrange duality -- 1.2 Fenchel duality and conic programming -- 1.3 Additive cost problems -- 1.4 Large number of constraints -- 1.5 Exact penalty functions -- 1.6 Notes, sources, and exercises -- 2. Optimization algorithms : an overview -- 2.1 Iterative descent algorithms -- 2.2 Approximation methods -- 2.3 Notes, sources, and exercises -- 3. Subgradient methods -- 3.1 Subgradients of convex real-valued functions -- 3.2 Convergence analysis of subgradient methods -- 3.3 E-subgradient methods -- 3.4 Notes, sources, and exercises -- 4. Polyhedral approximation methods -- 4.1 Outer linearization - cutting plane methods -- 4.2 Inner linearization - simplicial decomposition -- 4.3 Duality of outer and inner linearization -- 4.4 Generalized polyhedral approximation -- 4.5 Generalized simplicial decomposition -- 4.6 Polyhedral approximation for conic programming -- 4.7 Notes, sources, and exercises -- 5. Proximal algorithms -- 5.1 Basic theory of proximal algorithms -- 5.2 Dual proximal algorithms -- 5.3 Proximal algorithms with linearization -- 5.4 Alternating direction methods of multipliers -- 5.5 Notes, sources, and exercises -- 6. Additional algorithmic topics -- 6.1 Gradient projection methods -- 6.2 Gradient projection with extrapolation -- 6.3 Proximal gradient methods -- 6.4 Incremental subgradient proximal methods -- 6.5 Coordinate descent methods -- 6.6 Generalized proximal methods -- 6.7 E-descent and extended monotropic programming -- 6.8 Interior point methods -- 6.9 Notes, sources, and exercises -- Appendix A. Mathematical background -- Appendix B. Convex optimization theory : a summary
|
| 650 |
|
|
|a Optimisation mathématique
|
| 650 |
|
|
|a Fonctions convexes
|
| 650 |
|
|
|a Programmation non linéaire
|
| 997 |
|
|
|0 710865
|1 Livre papier
|a Ressource papier
|b INSA
|c 0/Blois/
|c 1/Blois/INSA CVL/
|z Blois, INSA CVL, 519 BER
|z Blois, INSA CVL, 519 BER
|
