-
2
-
-
0013344078
-
Training products of experts by minimizing contrastive divergence
-
Hinton, G.E. Training products of experts by minimizing contrastive divergence. Neural Computation, 14:1771-1800, 2002.
-
(2002)
Neural Computation
, vol.14
, pp. 1771-1800
-
-
Hinton, G.E.1
-
4
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
DOI 10.1162/neco.2006.18.7.1527
-
Hinton, G.E., Osindero, S., and Teh, Y.W. A fast learning algorithm for deep belief nets. Neural Computation, 18(7):1527-1554, 2006. (Pubitemid 44024729)
-
(2006)
Neural Computation
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.-W.3
-
5
-
-
22044434800
-
Estimation of non-normalized statistical models using score matching
-
Hyvärinen, A. Estimation of non-normalized statistical models using score matching. Journal of Machine Learning Research, 6:695-709, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 695-709
-
-
Hyvärinen, A.1
-
8
-
-
35148893484
-
A tutorial on energy-based learning
-
MIT Press
-
LeCun, Y., Chopra, S., Hadsell, R., Ranzato, M., and Huang, F.J. A tutorial on energy-based learning. In Predicting Structured Data. MIT Press, 2006.
-
(2006)
Predicting Structured Data
-
-
LeCun, Y.1
Chopra, S.2
Hadsell, R.3
Ranzato, M.4
Huang, F.J.5
-
9
-
-
80053455323
-
Inductive principles for restricted Boltzmann machine learning
-
Marlin, B.M., Swersky, K., Chen, B., and De Freitas, N. Inductive principles for restricted Boltzmann machine learning. In Artificial Intelligence and Statistics, pp. 509-516, 2010.
-
(2010)
Artificial Intelligence and Statistics
, pp. 509-516
-
-
Marlin, B.M.1
Swersky, K.2
Chen, B.3
De Freitas, N.4
-
10
-
-
77953520240
-
Learning to represent spatial transformations with factored higher-order Boltzmann machines
-
Memisevic, R. and Hinton, G.E. Learning to represent spatial transformations with factored higher-order Boltzmann machines. Neural Computation, 22:1473-1492, 2009.
-
(2009)
Neural Computation
, vol.22
, pp. 1473-1492
-
-
Memisevic, R.1
Hinton, G.E.2
-
11
-
-
77955989954
-
Modeling pixel means and covariances using factorized third-order Boltzmann machines
-
Ranzato, M. and Hinton, G.E. Modeling pixel means and covariances using factorized third-order Boltzmann machines. In IEEE Computer Vision and Pattern Recognition, pp. 2551-2558, 2010.
-
(2010)
IEEE Computer Vision and Pattern Recognition
, pp. 2551-2558
-
-
Ranzato, M.1
Hinton, G.E.2
-
12
-
-
84954424613
-
A unified energy-based framework for unsupervised learning
-
Ranzato, M., Boureau, Y.L., Chopra, S., and LeCun, Y. A unified energy-based framework for unsupervised learning. In Artificial Intelligence and Statistics, 2007.
-
(2007)
Artificial Intelligence and Statistics
-
-
Ranzato, M.1
Boureau, Y.L.2
Chopra, S.3
LeCun, Y.4
-
13
-
-
84862277721
-
Factored 3-way restricted Boltzmann machines for modeling natural images
-
Ranzato, M., Krizhevsky, A., and Hinton, G.E. Factored 3-way restricted Boltzmann machines for modeling natural images. In Artificial Intelligence and Statistics, pp. 621-628, 2010a.
-
(2010)
Artificial Intelligence and Statistics,.
, pp. 621-628
-
-
Ranzato, M.1
Krizhevsky, A.2
Hinton, G.E.3
-
14
-
-
85082120183
-
How to generate realistic images using gated MRF's
-
Ranzato, M., Mnih, V., and Hinton, G.E. How to generate realistic images using gated MRF's. In Advances in Neural Information Processing Systems, pp. 2002-2010, 2010b.
-
(2010)
Advances in Neural Information Processing Systems
, pp. 2002-2010
-
-
Ranzato, M.1
Mnih, V.2
Hinton, G.E.3
-
16
-
-
77952681438
-
A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets
-
Swersky, K., Chen, B., Marlin, B.M., and De Freitas, N. A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets. In Information Theory and Applications Workshop, pp. 1-10, 2010.
-
(2010)
Information Theory and Applications Workshop
, pp. 1-10
-
-
Swersky, K.1
Chen, B.2
Marlin, B.M.3
De Freitas, N.4
-
17
-
-
8344290493
-
Energy-based models for sparse overcomplete representations
-
Teh, Y.W., Welling, M., Osindero, S., and Hinton, G.E. Energy-based models for sparse overcomplete representations. Journal of Machine Learning Research, 4:1235-1260, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.4
, pp. 1235-1260
-
-
Teh, Y.W.1
Welling, M.2
Osindero, S.3
Hinton, G.E.4
-
18
-
-
56449086223
-
Training restricted Boltzmann machines using approximations to the likelihood gradient
-
Tieleman, T. Training restricted Boltzmann machines using approximations to the likelihood gradient. In International Conference on Machine Learning, pp. 1064-1071, 2008.
-
(2008)
International Conference on Machine Learning
, pp. 1064-1071
-
-
Tieleman, T.1
-
20
-
-
54749092170
-
80 million tiny images: A large dataset for non-parametric object and scene recognition
-
Torralba, A., Fergus, R., and Freeman, W.T. 80 million tiny images: A large dataset for non-parametric object and scene recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30:1958-1970, 2008.
-
(2008)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.30
, pp. 1958-1970
-
-
Torralba, A.1
Fergus, R.2
Freeman, W.T.3
-
21
-
-
79959575293
-
A connection between score matching and denoising autoencoders
-
To appear
-
Vincent, P. A connection between score matching and denoising autoencoders. Neural Computation, To appear, 2011.
-
(2011)
Neural Computation
-
-
Vincent, P.1
-
22
-
-
56449089103
-
Extracting and composing robust features with denoising autoencoders
-
Vincent, P., Larochelle, H., Bengio, Y., and Manzagol, P.A. Extracting and composing robust features with denoising autoencoders. In International Conference on Machine Learning, pp. 1096-1103, 2008.
-
(2008)
International Conference on Machine Learning
, pp. 1096-1103
-
-
Vincent, P.1
Larochelle, H.2
Bengio, Y.3
Manzagol, P.A.4
-
23
-
-
84898970768
-
Learning sparse topographic representations with products of student-t distributions
-
Welling, M., Hinton, G.E., and Osindero, S. Learning sparse topographic representations with products of student-t distributions. In Advances in Neural Information Processing Systems, 2003.
-
Advances in Neural Information Processing Systems, 2003
-
-
Welling, M.1
Hinton, G.E.2
Osindero, S.3
-
25
-
-
0000355193
-
Parametric inference for imperfectly observed Gibbsian fields
-
Younes, L. Parametric inference for imperfectly observed Gibbsian fields. Probability Theory and Related Fields, 82(4):625-645, 1989.
-
(1989)
Probability Theory and Related Fields
, vol.82
, Issue.4
, pp. 625-645
-
-
Younes, L.1
|