-
4
-
-
52449116403
-
A correlated topic model of Science
-
D. Blei and J. Lafferty. A correlated topic model of Science. Annals of Applied Stat., 1 (1): 17-35, 2007.
-
(2007)
Annals of Applied Stat.
, vol.1
, Issue.1
, pp. 17-35
-
-
Blei, D.1
Lafferty, J.2
-
5
-
-
33645025214
-
Hierarchical topic models and the nested Chinese restaurant process
-
D. Blei, T. Griffiths, M. Jordan, and J. Tenenbaum. Hierarchical topic models and the nested Chinese restaurant process. In NIPS, 2003.
-
(2003)
NIPS
-
-
Blei, D.1
Griffiths, T.2
Jordan, M.3
Tenenbaum, J.4
-
9
-
-
8644267631
-
GaP: A factor model for discrete data
-
ACM SI-GIR Conference on Research and Development in In-formation Retrieval
-
J. Canny. GaP: A factor model for discrete data. In Proceedings of the 27th Annual International ACM SI-GIR Conference on Research and Development in In-formation Retrieval, 2004.
-
(2004)
Proceedings of the 27th Annual International
-
-
Canny, J.1
-
11
-
-
85053970271
-
-
CRC press
-
Andrew Gelman, John B Carlin, Hal S Stern, David B Dunson, Aki Vehtari, and Donald B Rubin. Bayesian data analysis. CRC press, 2013.
-
(2013)
Bayesian Data Analysis
-
-
Gelman, A.1
Carlin, J.B.2
Stern, H.S.3
Dunson, D.B.4
Vehtari, A.5
Rubin, D.B.6
-
14
-
-
84884218772
-
Generalized spike-andslab priors for Bayesian group feature selection using expectation propagation
-
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, and Pierre Dupont. Generalized spike-andslab priors for bayesian group feature selection using expectation propagation. The Journal of Machine Learning Research, 14 (1): 1891-1945, 2013.
-
(2013)
The Journal of Machine Learning Research
, vol.14
, Issue.1
, pp. 1891-1945
-
-
Hernández-Lobato, D.1
Miguel Hernández-Lobato, J.2
Dupont, P.3
-
15
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
July. ISSN 0899-7667
-
G. Hinton, S. Osindero, and Y. Teh. A fast learning algorithm for deep belief nets. Neural Comput., 18 (7): 1527-1554, July 2006. ISSN 0899-7667.
-
(2006)
Neural Comput.
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.1
Osindero, S.2
Teh, Y.3
-
16
-
-
22944460748
-
Spike and slab variable selection: Frequentist and Bayesian strategies
-
H. Ishwaran and S. Rao. Spike and slab variable selection: Frequentist and Bayesian strategies. The Annals of Statistics, 33 (2): 730-773, 2005.
-
(2005)
The Annals of Statistics
, vol.33
, Issue.2
, pp. 730-773
-
-
Ishwaran, H.1
Rao, S.2
-
18
-
-
0033225865
-
Introduction to variational methods for graphical models
-
M. Jordan, Z. Ghahramani, T. Jaakkola, and L. Saul. Introduction to variational methods for graphical models. Machine Learning, 37: 183-233, 1999.
-
(1999)
Machine Learning
, vol.37
, pp. 183-233
-
-
Jordan, M.1
Ghahramani, Z.2
Jaakkola, T.3
Saul, L.4
-
20
-
-
0033592606
-
Learning the parts of objects by non-negative matrix factorization
-
October
-
D. Lee and H. Seung. Learning the parts of objects by non-negative matrix factorization. Nature, 401 (6755): 788-791, October 1999.
-
(1999)
Nature
, vol.401
, Issue.6755
, pp. 788-791
-
-
Lee, D.1
Seung, H.2
-
21
-
-
33749249041
-
Pachinko allocation: DAGstuctured mixture models of topic correlations
-
W. Li and A. McCallum. Pachinko allocation: DAGstuctured mixture models of topic correlations. In ICML, 2006.
-
(2006)
ICML
-
-
Li, W.1
McCallum, A.2
-
23
-
-
84919786239
-
Neural variational inference and learning in belief networks
-
A. Mnih and K. Gregor. Neural variational inference and learning in belief networks. In ICML, 2014.
-
(2014)
ICML
-
-
Mnih, A.1
Gregor, K.2
-
25
-
-
4243447828
-
-
Tech. Rep. CRG-TR-90-7: Department of Computer Science, University of Toronto
-
R. Neal. Learning stochastic feedforward networks. Tech. Rep. CRG-TR-90-7: Department of Computer Science, University of Toronto, 1990.
-
(1990)
Learning Stochastic Feedforward Networks
-
-
Neal, R.1
-
28
-
-
84919908080
-
Stochastic backpropagation and approximate inference in deep generative models
-
January
-
D. Rezende, S. Mohamed, and D. Wierstra. Stochastic backpropagation and approximate inference in deep generative models. ArXiv e-prints, January 2014.
-
(2014)
ArXiv E-prints
-
-
Rezende, D.1
Mohamed, S.2
Wierstra, D.3
-
30
-
-
84862286946
-
Deep boltzmann machines
-
R. Salakhutdinov and G. Hinton. Deep boltzmann machines. In AISTATS, pages 448-455, 2009.
-
(2009)
AISTATS
, pp. 448-455
-
-
Salakhutdinov, R.1
Hinton, G.2
-
33
-
-
77956556686
-
Replicated softmax: An undirected topic model
-
Y. Bengio D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors
-
Ruslan Salakhutdinov and Geoffrey Hinton. Replicated softmax: an undirected topic model. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 1607-1614. 2009.
-
(2009)
Advances in Neural Information Processing Systems
, vol.22
, pp. 1607-1614
-
-
Salakhutdinov, R.1
Hinton, G.2
-
34
-
-
84891700107
-
Fixed-form variational posterior approximation through stochastic linear regression
-
T. Salimans and D. Knowles. Fixed-form variational posterior approximation through stochastic linear regression. Bayesian Analysis, 8 (4): 837-882, 2013.
-
(2013)
Bayesian Analysis
, vol.8
, Issue.4
, pp. 837-882
-
-
Salimans, T.1
Knowles, D.2
-
37
-
-
84888183490
-
Modeling documents with a deep boltzmann machine
-
Nitish Srivastava, Ruslan Salakhutdinov, and Geoffrey Hinton. Modeling documents with a deep boltzmann machine. In UAI, 2013.
-
(2013)
UAI
-
-
Srivastava, N.1
Salakhutdinov, R.2
Hinton, G.3
|