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Keynote Talk
Workshop: 6th ICML Workshop on Automated Machine Learning (AutoML 2019)

Keynote by Peter Frazier: Grey-box Bayesian Optimization for AutoML

Peter Frazier


Bayesian optimization is a powerful and flexible tool for AutoML. While BayesOpt was first deployed for AutoML simply as a black-box optimizer, recent approaches perform grey-box optimization: they leverage capabilities and problem structure specific to AutoML such as freezing and thawing training, early stopping, treating cross-validation error minimization as multi-task learning, and warm starting from previously tuned models. We provide an overview of this area and describe recent advances for optimizing sampling-based acquisition functions that make grey-box BayesOpt significantly more efficient.

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