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Nicolas Le Roux and Yoshua Bengio.
Continuous Neural
Networks.
Technical Report 1281, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2006.
- 2
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Yoshua Bengio, Olivier Delalleau, and Nicolas Le Roux.
The Curse of Dimensionality for Local Kernel
Machines.
Technical Report 1258, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2005.
- 3
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Yoshua Bengio and Hugo Larochelle.
Non-Local Manifold Parzen
Windows.
Technical Report 1264, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2005.
- 4
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Y. Bengio, O. Delalleau, and N. Le Roux.
Efficient Non-Parametric Function Induction in
Semi-Supervised Learning.
Technical Report 1247, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2004.
- 5
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Y. Bengio, O. Delalleau, N. Le Roux, J.-F. Paiement, P. Vincent, and
M. Ouimet.
Learning eigenfunctions links spectral embedding
and kernel PCA.
Neural Computation, 16(10):2197-2219, 2004.
- 6
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Y. Bengio and M. Monperrus.
Discovering shared structure in manifold
learning.
Technical Report 1250, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2004.
- 7
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Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau,
Nicolas Le Roux, and Marie Ouimet.
Out-of-Sample Extensions for LLE, Isomap, MDS,
Eigenmaps, and Spectral
Clustering.
In Sebastian Thrun, Lawrence Saul, and Bernhard Schölkopf,
editors, Advances in Neural Information Processing Systems 16. MIT
Press, Cambridge, MA, 2004.
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Y. Bengio, J-F. Paiement, and P. Vincent.
Out-of-Sample Extensions for LLE, Isomap,
MDS, Eigenmaps, and Spectral Clustering.
Technical Report 1238, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2003.
- 9
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Y. Bengio, P. Vincent, J-F. Paiement, O. Delalleau, M. Ouimet, and N. Le Roux.
Spectral Clustering and Kernel PCA are Learning
Eigenfunctions.
Technical Report 1239, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2003.
- 10
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Y. Bengio, P. Vincent, and J.F. Paiement.
Learning Eigenfunctions of Similarity: Linking
Spectral Clustering and Kernel PCA.
Technical Report 1232, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2003.
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P. Vincent and Y. Bengio.
Locally Weighted Full Covariance Gaussian Density
Estimation.
Technical Report 1240, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2003.
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P. Vincent and Y. Bengio.
Manifold Parzen
Windows.
In Advances in Neural Information Processing Systems 15, 2003.
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Ronan Collobert, Samy Bengio, and Yoshua Bengio.
Parallel Mixture of SVMs for Very Large Scale
Problem.
Neural Computation, 2002.
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Ronan Collobert, Yoshua Bengio, and Samy Bengio.
Scaling Large Learning Problems with Hard Parallel
Mixtures, volume 2388 of Lecture Notes
in Computer Science.
Springer-Verlag, 2002.
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R. Collobert, S. Bengio, and Y. Bengio.
A Parallel Mixture of SVMs for Very Large Scale
Problems.
Technical Report 12, IDIAP, 2001.
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Pascal Vincent and Yoshua Bengio.
K-Local Hyperplane and Convex Distance Nearest
Neighbor Algorithms.
Technical Report 1197, Département d'informatique et recherche
opérationnelle, Université de Montréal, 2001.
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Pascal Vincent and Yoshua Bengio.
Kernel Matching Pursuit.
Machine Learning, 2001.
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Pascal Vincent and Yoshua Bengio.
A Neural Support Vector Network Architecture with
Adaptive Kernels.
In International Joint Conference on Neural Networks 2000,
volume V, pages 187-192, 2000.
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M. Bonneville, J. Meunier, Y. Bengio, and J.P. Soucy.
Support vector machines for improving the classication of brain pet
images.
In SPIE Medical Imaging, San Diego, 1998.
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Y. Bengio.
Radial basis functions for speech recognition.
In Speech Recognition and Understanding: Recent Advances, Trends
and Applications, pages 293-298. NATO Advanced Study Institute Series F:
Computer and Systems Sciences, 1990.
Labo Lisa
2006-08-23