Paper published in a book (Scientific congresses and symposiums)
Supervised learning to tune simulated annealing for in silico protein structure prediction
Marcos Alvarez, Alejandro; Maes, Francis; Wehenkel, Louis
2012 • In Verleysen, Michel (Ed.) ESANN 2012 proceedings, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
[en] Simulated annealing is a widely used stochastic optimization algorithm whose efficiency essentially depends on the proposal distribu- tion used to generate the next search state at each step. We propose to adapt this distribution to a family of parametric optimization problems by using supervised machine learning on a sample of search states derived from a set of typical runs of the algorithm over this family. We apply this idea in the context of in silico protein structure prediction.
Research Center/Unit :
Systèmes et Modélisation, GIGA-Research
Disciplines :
Computer science
Author, co-author :
Marcos Alvarez, Alejandro ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Maes, Francis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Supervised learning to tune simulated annealing for in silico protein structure prediction
Publication date :
25 April 2012
Event name :
ESANN 2012, 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
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