CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : The black box complexity of noisy-optimization is a great research area, with many real-world applications. Various criteria can be used: cumulative regret, simple regret, uniform rates. We discuss the impact of the use of second order information (improved rates under low noise assumption), or local sampling (slower simple regret convergence), or evolutionary optimization with revaluations (as efficient as mathematical programming in some cases with cumulative regret).
https://hal.inria.fr/hal-00844305
Contributor : Olivier Teytaud <>
Submitted on : Sunday, July 14, 2013 - 3:00:07 PM Last modification on : Wednesday, October 14, 2020 - 3:56:51 AM Long-term archiving on: : Tuesday, October 15, 2013 - 4:08:57 AM