HyLo: A Hybrid Low-Rank Natural Gradient Descent Method
Author:
Affiliation:
1. University of Toronto,Toronto,Canada
2. Rutgers University,Piscataway,NJ,US
3. University of Toronto,Toronto,CA,UK
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10046045/10045783/10046123.pdf?arnumber=10046123
Reference48 articles.
1. Efficient subsampled Gauss-Newton and natural gradient methods for training neural networks;ren;ArXiv Preprint,2019
2. A Gram-Gauss-Newton method learning overparameterized deep neural networks for regression problems;cai;Machine Learning,2019
3. Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks
4. Neural learning in structured parameter spaces - natural riemannian gradient;amari;Advances in neural information processing systems,1997
5. A Stochastic Approximation Method
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