Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization
This paper describes our approach to solving the black-box optimization challenge through learning search space partition for local Bayesian optimization. We develop an algorithm for low budget optimization. We further optimize the hyper-parameters of our algorithm using Bayesian optimization. Our approach has been ranked 3rd in the competition.
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