OptunaHub: A Platform for Black-Box Optimization
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918453897592832 |
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| author | Ozaki, Yoshihiko Watanabe, Shuhei Yanase, Toshihiko |
| author_facet | Ozaki, Yoshihiko Watanabe, Shuhei Yanase, Toshihiko |
| contents | Black-box optimization (BBO) underpins advances in domains such as AutoML and Materials Informatics, yet implementations of algorithms and benchmarks remain fragmented across research communities. We introduce OptunaHub (https://hub.optuna.org/), a community-oriented, decentralized platform for distributing BBO components under a unified Optuna-compatible interface. OptunaHub enables independent publication, discovery, and reuse of optimization algorithms and benchmark problems through a lightweight Python module, a contributor-driven registry, and a searchable web interface. The source code is publicly available in the \href{https://github.com/optuna/optunahub}{\texttt{optunahub}}, \href{https://github.com/optuna/optunahub-registry}{\texttt{optunahub-registry}}, and \href{https://github.com/optuna/optunahub-web}{\texttt{optunahub-web}} repositories under the Optuna organization on GitHub (https://github.com/optuna/). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_02798 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OptunaHub: A Platform for Black-Box Optimization Ozaki, Yoshihiko Watanabe, Shuhei Yanase, Toshihiko Machine Learning Artificial Intelligence Black-box optimization (BBO) underpins advances in domains such as AutoML and Materials Informatics, yet implementations of algorithms and benchmarks remain fragmented across research communities. We introduce OptunaHub (https://hub.optuna.org/), a community-oriented, decentralized platform for distributing BBO components under a unified Optuna-compatible interface. OptunaHub enables independent publication, discovery, and reuse of optimization algorithms and benchmark problems through a lightweight Python module, a contributor-driven registry, and a searchable web interface. The source code is publicly available in the \href{https://github.com/optuna/optunahub}{\texttt{optunahub}}, \href{https://github.com/optuna/optunahub-registry}{\texttt{optunahub-registry}}, and \href{https://github.com/optuna/optunahub-web}{\texttt{optunahub-web}} repositories under the Optuna organization on GitHub (https://github.com/optuna/). |
| title | OptunaHub: A Platform for Black-Box Optimization |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2510.02798 |