Zaslavski, Alexander J.
Numerical Optimization with Computational Errors
1. Introduction
Alexander J. Zaslavski
2. Subgradient Projection Algorithm
Alexander J. Zaslavski
3. The Mirror Descent Algorithm
Alexander J. Zaslavski
4. Gradient Algorithm with a Smooth Objective Function
Alexander J. Zaslavski
5. An Extension of the Gradient Algorithm
Alexander J. Zaslavski
6. Weiszfeld’s Method
Alexander J. Zaslavski
7. The Extragradient Method for Convex Optimization
Alexander J. Zaslavski
8. A Projected Subgradient Method for Nonsmooth Problems
Alexander J. Zaslavski
9. Proximal Point Method in Hilbert Spaces
Alexander J. Zaslavski
10. Proximal Point Methods in Metric Spaces
Alexander J. Zaslavski
11. Maximal Monotone Operators and the Proximal Point Algorithm
Alexander J. Zaslavski
12. The Extragradient Method for Solving Variational Inequalities
Alexander J. Zaslavski
13. A Common Solution of a Family of Variational Inequalities
Alexander J. Zaslavski
14. Continuous Subgradient Method
Alexander J. Zaslavski
15. Penalty Methods
Alexander J. Zaslavski
16. Newton’s Method
Alexander J. Zaslavski
Avainsanat: Mathematics, Calculus of Variations and Optimal Control; Optimization, Numerical Analysis, Operations Research, Management Science
- Tekijä(t)
- Zaslavski, Alexander J.
- Julkaisija
- Springer
- Julkaisuvuosi
- 2016
- Kieli
- en
- Painos
- 1
- Sarja
- Springer Optimization and Its Applications
- Sivumäärä
- 9 sivua
- Kategoria
- Eksaktit luonnontieteet
- Tiedostomuoto
- E-kirja
- eISBN (PDF)
- 9783319309217
- Painetun ISBN
- 978-3-319-30920-0