A Practical Guide to Training Restricted Boltzmann Machines

Author:

Hinton Geoffrey E.

Publisher

Springer Berlin Heidelberg

Reference24 articles.

1. Carreira-Perpignan, M.A., Hinton, G.E.: On contrastive divergence learning. In: Artificial Intelligence and Statistics (2005)

2. Freund, Y., Haussler, D.: Unsupervised learning of distributions on binary vectors using two layer networks. In: Advances in Neural Information Processing Systems 4, pp. 912–919. Morgan Kaufmann, San Mateo (1992)

3. Ghahramani, Z., Hinton, G.: The EM algorithm for mixtures of factor analyzers. Technical Report CRG-TR-96-1, University of Toronto (May 1996)

4. Hinton, G.E.: Relaxation and its role in vision. PhD Thesis (1978)

5. Hinton, G.E.: Training products of experts by minimizing contrastive divergence. Neural Computation 14(8), 1711–1800 (2002)

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