HAL - INRIA :: [inria-00369781, version 1] On the parallel speed-up of Estimation of Multivariate Normal Algorithm and Evolution Strategies

inria-00369781, version 1

On the parallel speed-up of Estimation of Multivariate Normal Algorithm and Evolution Strategies

Fabien Teytaud () ^1, 2, Olivier Teytaud () ^3, 4, 5

EvoNum (evostar workshop) EvoNum (2009)

Résumé : Motivated by parallel optimization, we experiment EDA-like adaptation-rules in the case of $\lambda$ large. The rule we use, essentially based on estimation of multivariate normal algorithm, is (i) compliant with all families of distributions for which a density estimation algorithm exists (ii) simple (iii) parameter-free (iv) better than current rules in this framework of $\lambda$ large. The speed-up as a function of $\lambda$ is consistent with theoretical bounds.

1 : Institut National de la Recherche en Informatique et en Automatique (INRIA FUTURS)
INRIA
2 : UFR Sciences - Université Paris-Sud XI
Université Paris XI - Paris Sud
3 : TAO (INRIA Futurs)
INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
4 : Laboratoire de Recherche en Informatique (LRI)
CNRS : UMR8623 – Université Paris XI - Paris Sud
5 : TAO (INRIA Saclay - Ile de France)
INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud

Collaboration : Grid'5000

inria-00369781, version 1
http://hal.inria.fr/inria-00369781
oai:hal.inria.fr:inria-00369781
Contributeur : Olivier Teytaud <>
Soumis le : Samedi 21 Mars 2009, 09:00:41
Dernière modification le : Mardi 24 Avril 2012, 09:26:31

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