Cmaes

Latest version: v0.11.1

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0.9.0

Highlights

CMA-ES with Margin is now available. It introduces a lower bound on the marginal probability associated with each discrete dimension so that samples can avoid being fixed to a single point. It can be applied to mixed spaces of continuous (float) and discrete (including integer and binary). This algorithm is proposed by Hamano, Saito, [nomuramasahir0](https://github.com/nomuramasahir0) (a maintainer of this library), and Shirakawa, has been nominated as best paper at GECCO'22 ENUM track.

0.8.2

CHANGES

* Fix dimensions of Warm starting CMA-ES (98).
* Thank you Yibinjiang for reporting the bug.

0.8.1

CHANGES

* Unset version constraint of numpy.
* Remove `extra_requires` for development.

0.8.0

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 |
| ---------------------- | ------------------ |
| ![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/

0.7.1

CHANGES

* Support Python 3.9 (84)
* Refactor constants definitions (85)
* Add tox.ini (86)
* Remove numpy from setup_requires (90)

0.7.0

CHANGES

New features

Separable CMA-ES is added at https://github.com/CyberAgent/cmaes/pull/82. It accelerates the search by ignoring the dependency of variables. This is inefficient if there is a strong dependency between variables; however, this technique significantly improves the performance if the dependency can be ignored.

| Benchmark |
| --- |
| ![68747470733a2f2f73746f726167652e676f6f676c65617069732e636f6d2f6b75726f62616b6f2d7265706f7274732f43796265724167656e742f636d6165732f7369782d68756d702d63616d656c2d34383231326238303339373266353830656439316335633838343262666631303331623136373336](https://user-images.githubusercontent.com/5564044/110200481-a3ed3b80-7ea1-11eb-9eb2-44267dec8429.png) |

* [R. Ros, N. Hansen. A Simple Modification in CMA-ES Achieving Linear Time and Space Complexity, PPSN, 2008.](https://hal.inria.fr/inria-00287367/document)

Dependency

* Drop Python 3.5 support (74)

Links

* PyPI: https://pypi.org/project/cmaes/0.7.0/

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