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Conference Papers Year : 2013

Noisy Optimization Complexity Under Locality Assumption

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Abstract

In spite of various recent publications on the subject, there are still gaps between upper and lower bounds in evolutionary optimization for noisy objective function. In this paper we reduce the gap, and get tight bounds within logarithmic factors in the case of small noise and no long-distance influence on the objective function.
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Dates and versions

hal-00755663 , version 1 (07-04-2013)

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  • HAL Id : hal-00755663 , version 1

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Jérémie Decock, Olivier Teytaud. Noisy Optimization Complexity Under Locality Assumption. FOGA - Foundations of Genetic Algorithms XII - 2013, Jan 2013, Adelaide, Australia. ⟨hal-00755663⟩
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