Reference : Bounds for Multistage Stochastic Programs using Supervised Learning Strategies
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/27715
Bounds for Multistage Stochastic Programs using Supervised Learning Strategies
English
Defourny, Boris [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore) >]
Ernst, Damien mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2009
Stochastic Algorithms: Foundations and Applications
Watanabe, Osamu
Zeugmann, Thomas
Springer
Lecture Notes in Computer Sciences; 5792
61-73
Yes
No
International
9783642049439
Stochastic Algorithms: Foundations and Applications. Fifth International Symposium, SAGA 2009
October 26-28, 2009
Hokkaido University
Sapporo
Japan
[en] Stochastic Programming ; Supervised Learning
[en] We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible decision policy, synthesized by a strategy relying on any scenario tree approximation from stochastic programming and on supervised learning techniques from machine learning.
Belgian Network DYSCO; FNRS-FRS
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/27715
10.1007/978-3-642-04944-6_6
http://www.springerlink.com/content/1700016r11964778
The original publication is available at www.springerlink.com .

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