Convex and Stochastic Optimization
This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting. It introduces and analyses the main algorithms for stochastic programs, while the theoreti...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2019, 2019
|
| Edition: | 1st ed. 2019 |
| Series: | Universitext
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 1 A convex optimization toolbox
- 2 Semidefinite and semiinfinite programming
- 3 An integration toolbox
- 4 Risk measures
- 5 Sampling and optimizing
- 6 Dynamic stochastic optimization
- 7 Markov decision processes
- 8 Algorithms
- 9 Generalized convexity and transportation theory
- References
- Index.