An Invariant Information Geometric Method for High-Dimensional Online Optimization
An Invariant Information Geometric Method for High-Dimensional Online Optimization
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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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Sample efficiency is crucial in optimization, particularly in black-box scenarios characterized by expensive evaluations and zeroth-order feedback. When computing resources are plentiful, Bayesian optimization is often favored over evolution strategies. In this paper, we introduce a full invariance oriented evolution strategies algorithm, derived f...
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An Invariant Information Geometric Method for High-Dimensional Online Optimization
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TN_cdi_proquest_journals_2910024711
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2910024711
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2331-8422
