CMA-ES and advanced adaptation mechanisms

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CMA-ES and Advanced Adaptation Mechanisms
GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference CompanionCMA-ES with Learning Rate Adaptation
The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful methods for solving continuous black-box optimization problems. A practically useful aspect of CMA-ES is that it can be used without hyperparameter tuning. However, ...
Evaluating the Population Size Adaptation Mechanism for CMA-ES on the BBOB Noiseless Testbed
GECCO '16 Companion: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference CompanionThe population size adaptation mechanism for CMA-ES is evaluated on the BBOB noiseless testbed. The population size is adapted on the basis of the estimated accuracy of the update of the distribution parameters, i.e., the mean vector and the covariance ...
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