OptunaHub: A Platform for Black-Box Optimization
This platform addresses the problem of fragmented research efforts for researchers and practitioners in fields like AutoML and Materials Informatics, though it is incremental as it builds on existing tools and concepts.
The authors tackled the fragmentation of black-box optimization research across domains by introducing OptunaHub, a community platform that centralizes methods and benchmarks, providing unified APIs and a web interface to promote cross-domain collaboration.
Black-box optimization (BBO) drives advances in domains such as AutoML and Materials Informatics, yet research efforts often remain fragmented across domains. We introduce OptunaHub (https://hub.optuna.org/), a community platform that centralizes BBO methods and benchmarks. OptunaHub provides unified Python APIs, a contributor package registry, and a web interface to promote searchability and cross-domain research. OptunaHub aims to foster a virtuous cycle of contributions and applications. The source code is publicly available in the optunahub, optunahub-registry, and optunahub-web repositories under the Optuna organization on GitHub (https://github.com/optuna/).