RNGD (Riemannian natural gradient methods)

Authors: Jiang Hu, Zaiwen Wen, [Ruicheng Ao]

Last page update: Dec. 4, 2022

Latest version: 1.0

Introduction

Riemannian natural gradient methods for solving negative log-probability loss over Riemannian manifold

min_{w in M} L(w) := 1/n sum_{i=1}^n log p(y_i|f(x_i,w)), where ${x_i,y_i}$ is the dataset with cardinality n.

References

• RNGD (Riemannian natural gradient methods)
  • J. Hu, R. Ao, A. M.-C. So, M. Yang, Z. Wen, "Riemannian Natural Gradient Methods, SIAM Journal on Scientific Computing 46.1 (2024): A204-A231."

The Authors

We hope that the package is useful for your application. If you have any bug reports or comments, please feel free to email one of the toolbox authors:

• Jiang Hu, hujiangopt at gmail.com
• Zaiwen Wen, wenzw at pku.edu.cn

Installation

startup

demo_mr_ml

License

Copyright (C) 2017, Jiang Hu, Zaiwen Wen

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see (http://www.gnu.org/licenses/)

Release Notes

• Version 1.0.0 (Dec. 4, 2022)
  • Initial version.