Adaptive Noisy Optimization

Philippe Rolet 1 Olivier Teytaud 1, 2
2 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In this paper, adaptive noisy optimization on variants of the noisy sphere model is considered, i.e. optimization in which the same algorithm is able to adapt to several frameworks, including some for which no bound has never been derived. Incidentally, bounds derived by [16] for noise quickly decreasing to zero around the optimum are extended to the more general case of a positively lower-bounded noise thanks to a careful use of Bernstein bounds (using empirical estimates of the variance) instead of Chernoff-like variants
Complete list of metadatas

Cited literature [17 references]  Display  Hide  Download
Contributor : Philippe Rolet <>
Submitted on : Tuesday, March 9, 2010 - 10:27:03 AM
Last modification on : Thursday, April 5, 2018 - 12:30:12 PM
Long-term archiving on : Friday, June 18, 2010 - 7:46:22 PM


Files produced by the author(s)


  • HAL Id : inria-00459017, version 1



Philippe Rolet, Olivier Teytaud. Adaptive Noisy Optimization. EvoStar 2010, Apr 2010, Istambul, Turkey. ⟨inria-00459017⟩



Record views


Files downloads