BriefGPT.xyz
Jun, 2014
基于最大似然的CMA-ES超参数在线自适应调整
Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES
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Ilya Loshchilov, Marc Schoenauer, Michèle Sebag, Nikolaus Hansen
TL;DR
本文研究了CMA-ES的在线自适应方法self-CMA-ES，旨在优化连续非线性问题的超参数设置，实验结果表明self-CMA-ES可以使得优化性能接近最优设置。
Abstract
The
covariance matrix adaptation evolution strategy
(CMA-ES) is widely accepted as a robust derivative-free
continuous optimization
algorithm for
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