Graduated Optimization of Black-Box Functions
2019-06-04Code Available0· sign in to hype
Weijia Shao, Christian Geißler, Fikret Sivrikaya
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Abstract
Motivated by the problem of tuning hyperparameters in machine learning, we present a new approach for gradually and adaptively optimizing an unknown function using estimated gradients. We validate the empirical performance of the proposed idea on both low and high dimensional problems. The experimental results demonstrate the advantages of our approach for tuning high dimensional hyperparameters in machine learning.