Convex optimization algorithms

Bewaard in:
Bibliografische gegevens
Hoofdauteur: Bertsekas, Dimitri P., 1942-
Formaat: Livre papier
Taal:Anglais
Gepubliceerd in: Nashua (N.H.) : Athena Scientific C 2015.
Onderwerpen:
Autres localisations: Voir dans le Sudoc
Inhoudsopgave:
  • 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