References

Random Search for Hyper-Parameter Optimization

James Bergstra & Yoshua Bengio (2012)

Journal of Machine Learning Research, 13, 281-305.

URL: https://jmlr.org/papers/v13/bergstra12a.html

Abstract. Shows that random search is substantially more efficient than grid search for hyperparameter tuning when only a few dimensions matter, since random sampling explores the important directions more thoroughly for the same computational budget.

Tags: hyperparameters random-search url-only

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