Learning Neural Surrogate Model for Warm-Starting Bayesian Optimization

ICLR 2020 Haotian ZhangJian SunZongben Xu

Bayesian optimization is an effective tool to optimize black-box functions and popular for hyper-parameter tuning in machine learning. Traditional Bayesian optimization methods are based on Gaussian process (GP), relying on a GP-based surrogate model for sampling points of the function of interest... (read more)

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