v0.8.0

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

• Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi. “Warm Starting CMA-ES for Hyperparameter Optimization”, AAAI. 2021.

Link

• PyPI: https://pypi.org/project/cmaes/0.8.0/