In machine learning, a hyperparameter is a parameter whose value is used to control learning process, and HPO is the problem of choosing a set of optimal hyperparameters for a learning algorithm.
Source: Algorithms for Hyper-Parameter OptimizationPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Bayesian Optimization | 30 | 16.95% |
BIG-bench Machine Learning | 13 | 7.34% |
Benchmarking | 10 | 5.65% |
Reinforcement Learning (RL) | 6 | 3.39% |
Federated Learning | 5 | 2.82% |
Image Classification | 5 | 2.82% |
Reinforcement Learning | 4 | 2.26% |
Language Modelling | 4 | 2.26% |
Fairness | 4 | 2.26% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |