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Eddie Bergman

2 accepted papers

2024

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

ICML 2024poster

With the increasing computational costs associated with deep learning, automated hyperparameter optimization methods, strongly relying on black-box Bayesian optimization (BO), face limitations. Freeze-thaw BO offers a promising grey-box alternative, strategically allocating scarce resources increme…

Cited by 10SourcePDFScholar
2023

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

NeurIPS 2023poster

Hyperparameters of Deep Learning (DL) pipelines are crucial for their downstream performance. While a large number of methods for Hyperparameter Optimization (HPO) have been developed, their incurred costs are often untenable for modern DL. Consequently, manual experimentation is still the most pre…