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All publications by James Martens
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Optimizing Neural Networks with Kronecker-factored Approximate Curvature
James Martens and Roger Grosse
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl and Geoffrey Hinton
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


On the Representational Efficiency of Restricted Boltzmann Machines
James Martens, Arkadev Chattopadhya, Toniann Pitassi and Richard Zemel
Advances in Neural Information Processing Systems 26, 2013


Estimating the Hessian by Back-propagating Curvature
James Martens, Ilya Sutskever and Kevin Swersky
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Generating Text with Recurrent Neural Networks
Ilya Sutskever, James Martens and Geoffrey E. Hinton
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Learning Recurrent Neural Networks with Hessian-Free Optimization
James Martens and Ilya Sutskever
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Learning the Linear Dynamical System with ASOS
James Martens
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Deep learning via Hessian-free optimization
James Martens
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Parallelizable Sampling of Markov Random Fields
James Martens and Ilya Sutskever
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010