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HyperBO+: Pre-training a universal hierarchical Gaussian process prior for Bayesian optimization
Zhou Fan · Xinran Han · Zi Wang

We present HyperBO+: a framework of pre-training a hierarchical Gaussian process that enables the same prior to work universally for Bayesian optimization on functions with different domains. We propose a two-step pre-training method and demonstrate its empirical success on challenging black-box function optimization problems with varied input dimensions and search spaces.

Author Information

Zhou Fan (Harvard University)
Xinran Han (Harvard University)
Zi Wang (Google Brain)

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