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James Martens
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Publications
- 2019
- [c17]Guodong Zhang, James Martens, Roger B. Grosse:
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks. NeurIPS 2019: 8080-8091 - [c16]Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse:
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. NeurIPS 2019: 8194-8205 - [i9]Guodong Zhang, James Martens, Roger B. Grosse:
Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks. CoRR abs/1905.10961 (2019) - [i7]Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse:
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. CoRR abs/1907.04164 (2019) - 2018
- [c13]Zachary Nado, Jasper Snoek, Roger B. Grosse, David Duvenaud, Bowen Xu, James Martens:
Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure. ICLR (Workshop) 2018 - 2017
- [c11]Jimmy Ba, Roger B. Grosse, James Martens:
Distributed Second-Order Optimization using Kronecker-Factored Approximations. ICLR (Poster) 2017 - 2016
- [c10]Roger B. Grosse, James Martens:
A Kronecker-factored approximate Fisher matrix for convolution layers. ICML 2016: 573-582 - [i5]Roger B. Grosse, James Martens:
A Kronecker-factored approximate Fisher matrix for convolution layers. CoRR abs/1602.01407 (2016) - 2015
- [c9]James Martens, Roger B. Grosse:
Optimizing Neural Networks with Kronecker-factored Approximate Curvature. ICML 2015: 2408-2417 - [i4]James Martens, Roger B. Grosse:
Optimizing Neural Networks with Kronecker-factored Approximate Curvature. CoRR abs/1503.05671 (2015)
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