Theoretical Analysis of Explicit Averaging and Novel Sign Averaging in Comparison-Based Search
Theoretical Analysis of Explicit Averaging and Novel Sign Averaging in Comparison-Based Search
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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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In black-box optimization, noise in the objective function is inevitable. Noise disrupts the ranking of candidate solutions in comparison-based optimization, possibly deteriorating the search performance compared with a noiseless scenario. Explicit averaging takes the sample average of noisy objective function values and is widely used as a simple...
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Theoretical Analysis of Explicit Averaging and Novel Sign Averaging in Comparison-Based Search
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TN_cdi_proquest_journals_2918654846
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2918654846
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2331-8422
