I am a postdoc in the Machine Learning and Perception Group at Microsoft Research. I am mainly interested in designing new architectures of deep neural networks and efficient ways to train them.
Previously, I was a PhD student at the LISA laboratory in University of Montreal under the supervision of Yoshua Bengio.
Here is my Curriculum Vitae, in which you will find my email address.
Publications
PhD thesis
§ Avancées théoriques sur la représentation et l’optimisation des réseaux de neurones (in French)
N. Le Roux
University of Montreal
Peer-reviewed articles
§ Representational Power of Restricted Boltzmann Machines and Deep Belief Networks (2008)
N. Le Roux and Y. Bengio
Neural Computation, volume 20, p. 1631-1649
§ Learning the 2-D Topology of Images (2008)
N. Le Roux, Y. Bengio, P. Lamblin, M. Joliveau and B. Kegl
In Advances in Neural Information Processing Systems 20, MIT Press, Cambridge, MA
§ Topmoumoute Online Natural Gradient Algorithm (2008)
N. Le Roux, P.A. Manzagol and Y. Bengio
In Advances in Neural Information Processing Systems 20, MIT Press, Cambridge, MA
§ Continuous Neural Networks (2007)
N. Le Roux and Y. Bengio
In Proceedings of the Eleventh International Workshop on Artificial Intelligence and Statistics
§ Convex Neural Networks (2006)
Y. Bengio, N. Le Roux, P. Vincent, O. Delalleau and P. Marcotte
In Advances in Neural Information Processing Systems 18, MIT Press, Cambridge, MA
§ The Curse of Highly Variable Functions for Local Kernel Machines (2006)
Y. Bengio, O. Delalleau, and N. Le Roux
In Advances in Neural Information Processing Systems 18, MIT Press, Cambridge, MA
§ Efficient Non-Parametric Function Induction in Semi-Supervised Learning (2006)
O. Delalleau Y. Bengio, and N. Le Roux
In Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics
§ Learning Eigenfunctions Links Spectral Embedding and Kernel PCA (2004)
Y. Bengio, O. Delalleau, N. Le Roux, J.-F. Paiement, M. Ouimet and P. Vincent
In Neural Computation, volume 16, issue 10
§ Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering (2004)
Y. Bengio, J.-F. Paiement, P. Vincent, O. Delalleau, N. Le Roux and M. Ouimet
In Advances in Neural Information Processing Systems 16, MIT Press, Cambridge, MA
Book chapters
§ Spectral Dimensionality Reduction (2006)
Y. Bengio, O. Delalleau, N. Le Roux, J.-F. Paiement, P. Vincent and M. Ouimet
Chapter of the book Feature Extraction, Foundations and Applications by Isabelle Guyon, Steve Gunn, Masoud Nikravesh, and Lofti Zadeh
§ Label propagation and quadratic criterion (2005)
Y. Bengio, O. Delalleau and N. Le Roux
Chapter of the book Semi-supervised learning by O. Chapelle, Bernhard Schölkopf and Alexander Zien
§ Large-scale algorithms (2005)
O. Delalleau Y. Bengio, and N. Le Roux
Chapter of the book Semi-supervised learning by O. Chapelle, Bernhard Schölkopf and Alexander Zien
