  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.
