CHANGES
New features
Warm-starting CMA-ES is now available. It estimates a promising distribution, then generates parameters of the multivariate gaussian distribution used for the initialization of CMA-ES, so that you can exploit optimization results from a similar optimization task. This algorithm is proposed by nmasahiro, a maintainer of this library, and accepted at AAAI 2021.
| Rot Ellipsoid | Ellipsoid |
| ---------------------- | ------------------ |
| ![rot-ellipsoid](https://user-images.githubusercontent.com/5564044/106723051-0c01f500-664a-11eb-8f37-ece937a3e9a6.png) | ![quadratic](https://user-images.githubusercontent.com/5564044/106723041-09070480-664a-11eb-817a-b0292f2e0201.png) |
* [Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi. “Warm Starting CMA-ES for Hyperparameter Optimization”, AAAI. 2021.](https://arxiv.org/abs/2012.06932)
Link
* PyPI: https://pypi.org/project/cmaes/0.8.0/