Bayesian Contextual Bandits for Hyper Parameter Optimization
Hyper parameter optimization (HPO) is a crucial step in modern machine learning systems. Bayesian optimization (BO) has shown great promise in HPO, where the parameter evaluation is conducted through a black-box optimization procedure. However, the main drawback of BO lies in the expensive computati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9017927/ |