Comparison-based natural gradient optimization in high dimension-Reference-Cited by-同舟云学术

Comparison-based natural gradient optimization in high dimension

Published:2014-07-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation
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Author:

Akimoto Youhei¹,Auger Anne²,Hansen Nikolaus²

Affiliation:

1. Shinshu University, Nagano, Japan

2. INRIA, Orsay, France

Funder

Agence Nationale de la Recherche

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2576768.2598258

Reference21 articles.

1. Theoretical Foundation for CMA-ES from Information Geometry Perspective

2. Natural Gradient Works Efficiently in Learning

3. Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons

4. Y. Ollivier L. Arnold A. Auger and N. Hansen. Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. arXiv:1106.3708 2011. Y. Ollivier L. Arnold A. Auger and N. Hansen. Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. arXiv:1106.3708 2011.

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