Learning algorithms for separable approximations of stochastic optimization problems
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: Stochastic Programming E-Print Series, 18
- Ereignis
-
Veröffentlichung
- (wo)
-
Berlin
- (wer)
-
Humboldt-Universität zu Berlin
- (wann)
-
2002
- Urheber
-
Powell, Warren
Ruszczynski, Andrzej
Topaloglu, Huseyin
- DOI
-
10.18452/8282
- URN
-
urn:nbn:de:kobv:11-10058600urn:nbn:de:kobv:11-10058611
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:03 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Powell, Warren
- Ruszczynski, Andrzej
- Topaloglu, Huseyin
- Humboldt-Universität zu Berlin
Entstanden
- 2002
Ähnliche Objekte (12)
Optimization : algorithms and consistent approximations
Convergence in distribution of randomized algorithms: the case of partially separable optimization
Parallel stochastic optimization based on descent algorithms
Sampling based approximation algorithms for multi-stage stochastic optimization
Is UK Risky Money Weakly Separable? A Stochastic Approach
Galerkin approximations for the stochastic Burgers equation
Galerkin Approximations for the Stochastic Burgers Equation
Output Optimization by Lie Bracket Approximations
A Comparative Study of Decomposition Algorithms for Stochastic Combinatorial Optimization
Approximation algorithms for 2-stage and multi-stage stochastic optimization
One-Step Approximations For Stochastic Functional Differential Equations
Variance reduction in sample approximations of stochastic programs
Optimization : algorithms and consistent approximations
Convergence in distribution of randomized algorithms: the case of partially separable optimization
Parallel stochastic optimization based on descent algorithms
Sampling based approximation algorithms for multi-stage stochastic optimization
Is UK Risky Money Weakly Separable? A Stochastic Approach
Galerkin approximations for the stochastic Burgers equation
Galerkin Approximations for the Stochastic Burgers Equation
Output Optimization by Lie Bracket Approximations
A Comparative Study of Decomposition Algorithms for Stochastic Combinatorial Optimization
Approximation algorithms for 2-stage and multi-stage stochastic optimization
One-Step Approximations For Stochastic Functional Differential Equations
Variance reduction in sample approximations of stochastic programs
Optimization : algorithms and consistent approximations
Convergence in distribution of randomized algorithms: the case of partially separable optimization
Parallel stochastic optimization based on descent algorithms
Sampling based approximation algorithms for multi-stage stochastic optimization
Is UK Risky Money Weakly Separable? A Stochastic Approach
Galerkin approximations for the stochastic Burgers equation
Galerkin Approximations for the Stochastic Burgers Equation
Output Optimization by Lie Bracket Approximations
A Comparative Study of Decomposition Algorithms for Stochastic Combinatorial Optimization
Approximation algorithms for 2-stage and multi-stage stochastic optimization
One-Step Approximations For Stochastic Functional Differential Equations