CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and N...
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems?
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful methods for solving black-box continuous optimization problems. One practically useful aspect of the CMA-ES is that it can be used without hyperparameter tuning. However, the hyperparameter settings still have a considerable impact, especially for difficult t...
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CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems?
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TN_cdi_proquest_journals_2802661112
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2802661112
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2331-8422
DOI
10.48550/arxiv.2304.03473
