James Martens - Concepedia

Author

James Martens

University of Toronto

Also Known As

J Martens, J. W. Martens, James Martens, Martens, James

Publications

8.3K

Citations

H-Index

Concepts

All Affiliations

University of Toronto Google (United States)University of California, Berkeley

About

James Martens is an author at University of Toronto specializing in engineering, machine learning, and computer science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	19	22	1.9K
2	Arts	1	1	32
3	Business	1	1	81
4	Medicine	1	1	30
5	Social Sciences	1	1	48

James Martens

Publications

Citations

H-Index

Page 1

	Year	Citations
On the importance of initialization and momentum in deep learning Ilya Sutskever, James Martens, George E. Dahl,	2013	3.5K
Generating Text with Recurrent Neural Networks Ilya Sutskever, James Martens, Geoffrey E. Hinton	2011	1.2K
Deep learning via Hessian-free optimization James Martens	2010	714
Learning Recurrent Neural Networks with Hessian-Free Optimization James Martens, Ilya Sutskever	2011	532
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens, Roger Grosse arXiv (Cornell University) Model OptimizationEngineeringMachine LearningData SciencePattern Recognition	2015	289
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan, Luke Vilnis, Quoc V. Le, arXiv (Cornell University) Llm Fine-tuningConvolutional Neural NetworkEngineeringMachine LearningRecurrent Neural Network	2015	265
New Insights and Perspectives on the Natural Gradient Method James Martens Journal of Machine Learning Research Numerical AnalysisMathematical ProgrammingEngineeringMachine LearningNatural Gradient Descent	2020	256
Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens, Roger Grosse International Conference on Machine Learning Model OptimizationEngineeringMachine LearningData SciencePattern Recognition	2015	218
Adversarial Robustness through Local Linearization Chongli Qin, James Martens, Sven Gowal, Neural Information Processing Systems Adversarial ExamplesData AugmentationConvolutional Neural NetworkEngineeringMachine Learning	2019	128
New insights and perspectives on the natural gradient method James Martens arXiv (Cornell University) Numerical AnalysisMathematical ProgrammingEngineeringMachine LearningNatural Gradient Descent	2014	94

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