Cargando…
Accelerating Hyperparameter Optimization of Deep Neural Network via Progressive Multi-Fidelity Evaluation
Deep neural networks usually require careful tuning of hyperparameters to show their best performance. However, with the size of state-of-the-art neural networks growing larger, the evaluation cost of the traditional Bayesian optimization has become unacceptable in most cases. Moreover, most practic...
| Autores principales: | , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206157/ http://dx.doi.org/10.1007/978-3-030-47426-3_58 |