Guided evolutionary strategies: augmenting random search with surrogate gradients

international conference on machine learning, 2019.

Cited by: 35|Bibtex|Views53
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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

Many applications in machine learning require optimizing a function whose true gradient is unknown, but where surrogate gradient information (directions that may be correlated with, but not necessarily identical to, the true gradient) is available instead. This arises when an approximate gradient is easier to compute than the full gradi...More

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