Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper−Parameters
Bayesian optimisation has gained great popularity as a tool for optimising the parameters of machine learning algorithms and models. Somewhat ironically, setting up the hyper-parameters of Bayesian optimisation methods is notoriously hard. While reasonable practical solutions have been advanced, the...
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| 格式: | Report |
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University of Oxford
2014
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