Greedy layer-wise training of deep networks (2007)

by Yoshua Bengio , Pascal Lamblin , Dan Popovici , Hugo Larochelle , Université De Montréal , Montréal Québec
Venue:In NIPS
Citations:187 - 32 self

Active Bibliography

1 Representational Power of Restricted Boltzmann Machines and Deep Belief Networks – Nicolas Le Roux, Yoshua Bengio
21 Representational power of restricted boltzmann machines and deep belief networks – Nicolas Le Roux, Yoshua Bengio - 2007
42 Exploring strategies for training deep neural networks – Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, Pascal Lamblin, Léon Bottou
2 Shallow vs. Deep Sum-Product Networks – Olivier Delalleau, Université De Montréal, Yoshua Bengio, Université De Montréal
77 Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition – George E. Dahl, Student Member, Dong Yu, Senior Member, Li Deng, Alex Acero - 2012
9 Representation Learning: A Review and New Perspectives – Yoshua Bengio, Aaron Courville, Pascal Vincent - 2012
The Utility of Knowledge Transfer with Noisy Training Sets – Steven Gutstein, Olac Fuentes, Eric Freudenthal
Visual Object Recognition Using Generative Models of Images – Vinod Nair - 2010
3 On the expressive power of deep architectures – Yoshua Bengio, Olivier Delalleau - 2011
Extraction hiérarchique de caractéristiques pour l’apprentissage à partir de données complexes en haute dimension – Olivier Delalleau - 2008
An Introduction to Deep Learning – Ludovic Arnold, Sébastien Rebecchi, Sylvain Chevallier, Hélène Paugam-moisy
2 Large margin classification in infinite neural networks – Youngmin Cho, Lawrence K. Saul
iv TABLE OF CONTENTS Signature Page.................................. Dedication..................................... Table of Contents................................. – Youngmin Cho - 2012
20 Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning – Mohammad Norouzi, Mani Ranjbar, Greg Mori
Journal of Logic and Computation Advance Access published October 26, 2009 Relevance Realization and the Emerging – unknown authors
Learning Long-Range Vision for an Offroad Robot – Raia Thaïs Hadsell - 2008
NOTE Communicated by Yoshua Bengio Deep, Narrow Sigmoid Belief Networks Are Universal – Ilya Sutskever, Geoffrey E. Hinton
On Herding in Deep Networks – Laurens Van Der Maaten - 2010
16 Dimensionality Reduction: A Comparative Review – L.J.P. van der Maaten, E. O. Postma, H. J. van den Herik - 2008