HyLo: A Hybrid Low-Rank Natural Gradient Descent Method

Author:

Mu Baorun1,Soori Saeed1,Can Bugra2,Gürbüzbalaban Mert2,Dehnavi Maryam Mehri3

Affiliation:

1. University of Toronto,Toronto,Canada

2. Rutgers University,Piscataway,NJ,US

3. University of Toronto,Toronto,CA,UK

Publisher

IEEE

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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