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.


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