715 citations · 1.2k across the 4 of their papers we have counts for
4 papers
The Loss Surfaces of Multilayer Networks
Anna Choromanska, Mikael Henaff, Michael Mathieu +2
We study the connection between the highly non-convex loss function of a simple model of the fully-connected feed-forward neural network and the Hamiltonian of the spherical spin-g…
Learning Longer Memory in Recurrent Neural Networks
Tomas Mikolov, Armand Joulin, Sumit Chopra +2
Recurrent neural network is a powerful model that learns temporal patterns in sequential data. For a long time, it was believed that recurrent networks are difficult to train using…
Fast Convolutional Nets With fbfft: A GPU Performance Evaluation
Nicolas Vasilache, Jeff Johnson, Michael Mathieu +3
We examine the performance profile of Convolutional Neural Network training on the current generation of NVIDIA Graphics Processing Units. We introduce two new Fast Fourier Transfo…
Fast Approximation of Rotations and Hessians matrices
Michael Mathieu, Yann LeCun
A new method to represent and approximate rotation matrices is introduced. The method represents approximations of a rotation matrix with linearithmic complexity, i.e. with $\f…