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https://github.com/SimonBlanke/Gradient-Free-Optimizers
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
https://github.com/SimonBlanke/Gradient-Free-Optimizers
bayesian-optimization blackbox-optimization constrained-optimization evolution-strategies gradient-free-optimization hill-climbing hyperactive hyperparameter-optimization machine-learning meta-heuristic nelder-mead optimization particle-swarm-optimization random-search simulated-annealing tree-of-parzen-estimator
Last synced: 5 days ago
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Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
- Host: GitHub
- URL: https://github.com/SimonBlanke/Gradient-Free-Optimizers
- Owner: SimonBlanke
- License: mit
- Created: 2020-04-04T06:35:55.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-10-21T19:17:48.000Z (20 days ago)
- Last Synced: 2024-10-22T12:11:27.140Z (19 days ago)
- Topics: bayesian-optimization, blackbox-optimization, constrained-optimization, evolution-strategies, gradient-free-optimization, hill-climbing, hyperactive, hyperparameter-optimization, machine-learning, meta-heuristic, nelder-mead, optimization, particle-swarm-optimization, random-search, simulated-annealing, tree-of-parzen-estimator
- Language: Python
- Homepage: https://simonblanke.github.io/gradient-free-optimizers-documentation
- Size: 38.2 MB
- Stars: 1,204
- Watchers: 21
- Forks: 84
- Open Issues: 11
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Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md