Sherpa: Robust Hyperparameter Optimization for Machine Learning

Sherpa is a hyperparameter optimization library for machine learning models. It is specifically designed for problems with computationally expensive, iterative function evaluations, such as the hyperparameter tuning of deep neural networks.

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Lars Hertela, Julian Collado, Peter Sadowski, Jordan Ott, Pierre Baldi (2024). Dataset: Sherpa: Robust Hyperparameter Optimization for Machine Learning. https://doi.org/10.57702/191btk3v

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2005.04048
Author Lars Hertela
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Julian Collado
Peter Sadowski
Jordan Ott
Pierre Baldi
Homepage https://github.com/sherpa-ai/sherpa