Neuromorphic adaptations of restricted Boltzmann machines and deep belief networks

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2013, Pages

  Pedroni, Bruno U ^a   Das, Srinjoy ^a   Neftci, Emre ^a   Kreutz Delgado, Kenneth ^a   Cauwenberghs, Gert ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMIC EFFICIENCIES; DEEP BELIEF NETWORKS; DIMENSIONALITY REDUCTION; LARGE-SCALE NETWORK; RESTRICTED BOLTZMANN MACHINE; SAMPLING ALGORITHM; SPIKING NEURON; VERY LARGE-SCALE INTEGRATION;

ALGORITHMS; NEURAL NETWORKS;

LOW POWER ELECTRONICS;

EID: 84893546078     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2013.6707067     Document Type: Conference Paper

References (9)

1. Hinton, G.E., Sejnowski, T.J., and Ackley, D.H., "Boltzmann Machines: Constraint Satisfaction Networks that Learn", Technical Report CMUCS84119, May 1984.
2. Mead, C., "Analog VLSI and Neural Systems". Reading, MA: AddisonWesley, 1989.
3. Aarts, E.H.L. and Korst, J.H.M., "Boltzmann Machines and Their Applications", PARLE Parallel Architectures and Languages, Europe, 1987.
4. Ackley, D.H., Hinton, G.E., and Sejnowski, T.J., "A Learning Algorithm for Boltzmann Machines". Cognitive 9, pp. 147-169, 1985.
5. Smolensky, P., "Information processing in dynamical systems: Foundations of harmony theory". Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volume 1: Foundations. Cambridge, MA: MIT Press/Bradford Books, pp. 194- 281, 1986.
6. Hinton, G.E., "Training products of experts by minimizing contrastive divergence". Neural Computation, 14(8), pp. 1771-1800, August 2002.
7. Hinton, G.E., Osindero, S., and Teh, Y.W., "A fast learning algorithm for deep belief nets", Neural Computation, 18:1527-1554, 2006.
8. Buesing, L., Bill, J., Nessler, B., and Maass, W., "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons", PLOS Computational Biology, Volume 7, Issue 11, November 2011.
9. La Rochelle, H. and Bengio, Y., "Classification using Discriminative Restricted Boltzmann Machines", Proceedings of the 25th International Conference on Machine Learning, Helsinki, Finland, 2008.