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Results tagged with bayesian-optimization
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user 376811
Bayesian optimization is a family of global optimization methods which use information about previously-computed values of the function to make inference about which function values are plausibly optima. Its applications include computer experiments and hyper-parameter optimization in some machine learning models.
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Monte Carlo Dropout as surrogate model for Bayesian Optimization
I am interested in using Monte Carlo Dropout as a surrogate model for Bayesian optimization. I noticed that the paper states:
The use of dropout (and its variants) in NNs can be interpreted as a Baye …
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