Papers › PHS: A Toolbox for Parallel Hyperparameter Search

PHS: A Toolbox for Parallel Hyperparameter Search

26 Feb 2020arXiv:2002.11429archive 2025-07-28

Peter Michael Habelitz, Janis Keuper

We introduce an open source python framework named PHS - Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside the target function. Possible applications appear in expensive to evaluate numerical computations which strongly depend on hyperparameters such as machine learning. Bayesian optimization is chosen as a sample efficient method to propose the next query set of parameters.

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BIG-bench Machine LearningBayesian OptimizationHyperparameter Optimization

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