Towards Automatic Bayesian Optimization: A first step involving acquisition functions

21 Mar 2020Eduardo C. Garrido MerchánLuis C. Jariego Pérez

Bayesian Optimization is the state of the art technique for the optimization of black boxes, i.e., functions where we do not have access to their analytical expression nor its gradients, they are expensive to evaluate and its evaluation is noisy. The most popular application of bayesian optimization is the automatic hyperparameter tuning of machine learning algorithms, where we obtain the best configuration of machine learning algorithms by optimizing the estimation of the generalization error of these algorithms... (read more)

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