Riemannian Natural Gradient Methods-Reference-Cited by-同舟云学术

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Riemannian Natural Gradient Methods

Published:2024-01-22 Issue:1 Volume:46 Page:A204-A231
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Hu Jiang¹^ORCID,Ao Ruicheng²,So Anthony Man-Cho¹^ORCID,Yang Minghan³,Wen Zaiwen⁴^ORCID

Affiliation:

1. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.

2. Peking University, Beijing, China.

3. Beijing International Center for Mathematical Research, Peking University, China.

4. Corresponding author. Beijing International Center for Mathematical Research, Center for Data Science and Changsha Institute for Computing and Digital Economy, Peking University, Beijing, China.

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference47 articles.

1. Optimization Algorithms on Matrix Manifolds

2. An Extrinsic Look at the Riemannian Hessian

3. Projection-like Retractions on Matrix Manifolds

4. Natural Gradient Works Efficiently in Learning

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