Performance Improvements in Natural Gradient Descent Method
Author:
Affiliation:
1. Anhui University,AHU-IAI AI Joint Laboratory,Hefei,Anhui,P. R. China,230601
2. Institute of Artificial Intelligence, Hefei Comprehensive National Science Center,Hefei,Anhui,P. R. China,230088
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10548022/10548040/10549159.pdf?arnumber=10549159
Reference11 articles.
1. Recent Advances in Stochastic Gradient Descent in Deep Learning
2. Efficient Natural Gradient Descent Methods for Large-Scale PDE-Based Optimization Problems
3. Doping a Mott insulator: Physics of high-temperature superconductivity
4. New insights and perspectives on the natural gradient method;Martens;Journal of Machine Learning Research,2020
5. Sinkhorn natural gradient for generative models;Shen;Advances in Neural Information Processing Systems,2020
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