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2
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Training Products of Experts by Maximizing Contrastive Likelihood
– Geoffrey E. Hinton
- 1999
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ARTICLE Training Products of Experts by Minimizing Contrastive Divergence
– Communicated Javier Movellan, Geoffrey E. Hinton
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2
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Modelling High-Dimensional Data by Combining Simple Experts
– Geoffrey E. Hinton
- 2000
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112
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Products of Experts
– Geoffrey E. Hinton
- 1999
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5
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Reinforcement learning for factored markov decision processes
– Brian Sallans
- 2002
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27
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Recognizing hand-written digits using hierarchical products of experts
– Guy Mayraz, Geoffrey E. Hinton
- 2001
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7
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An Introduction to Variational Methods for Graphical Methods
– Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul
- 1998
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165
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The Helmholtz Machine
– Peter Dayan, Geoffrey E. Hinton, Radford M. Neal, Richard S. Zemel
- 1995
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7
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Quick Training of Probabilistic Neural Nets by Importance Sampling
– Yoshua Bengio, Jean-Sébastien Senécal
- 2003
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2
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Learning to Parse Images
– Yee Whye Teh
- 2000
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Two Distributed-State Models For Generating High-Dimensional Time Series ∗
– Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis, Yoshua Bengio, C○ Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis Taylor
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5
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Learning Generative Models with the Up-Propagation Algorithm
– Jong-Hoon Oh, H. Sebastian Seung
- 1998
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What kind of a graphical model is the brain?
– Geoffrey E. Hinton
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23
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Factor analysis using delta-rule wake-sleep learning
– Radford M. Neal, Peter Dayan
- 1997
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70
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Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm
– Randall C. O'Reilly
- 1996
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290
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Connectionist Learning Procedures
– Geoffrey E. Hinton
- 1989
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17
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Variational learning in non-linear Gaussian belief networks
– Brendan J. Frey, Geoffrey E. Hinton
- 1999
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Massively Parallel Probabilistic Reasoning with Boltzmann Machines
– Petri MyllymÄki, Petri Myllym Äki
- 1999
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2
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Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex
– Szabolcs Káli, Peter Dayan
- 2000
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