Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks
Compared to the traditional machine learning models, deep neural networks (DNN) are known to be highly sensitive to the choice of hyperparameters. While the required time and effort for manual tuning has been rapidly decreasing for the well developed and commonly used DNN architectures, undoubtedly...
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| Автори: | , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2020-01-01
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| Серія: | IEEE Access |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/9037259/ |
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