PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bandit-based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis
Philippe Rolet and Olivier Teytaud
LION4 Proceedings 2010.

Abstract

We show complexity bounds for noisy optimization, in frameworks in which noise is stronger than in previously published papers[19]. We also propose an algorithm based on bandits (variants of [16]) that reaches the bound within logarithmic factors. We emphasize the differences with empirical derived published algorithms.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5882
Deposited By:Philippe Rolet
Deposited On:08 March 2010