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Extensions of Bayesian Optimization for Real-World Applications
Bayesian Optimization (BO) is a popular approach in statistics and machine learning for the global optimization of expensive blackbox functions. It has strong theoretical foundations and also yields state-of-the-art empirical results for optimizing functions with few all-continuous inputs. However, many blackbox optimization problems in real ...
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