Asynchronous network of cellular automaton-based neurons for efficient implementation of Boltzmann machines

Author:

Matsubara Takashi1,Uehara Kuniaki1

Affiliation:

1. Graduate School of System informatics, Kobe University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Reference31 articles.

1. [1] Y. Bengio, “Learning Deep Architectures for AI,” Foundations and Trends in Machine Learning, vol. 2, no. 1, pp. 1-127, 2009.

2. [2] J. Schmidhuber, “Deep learning in neural networks: An overview,” Neural Networks, vol. 61, pp. 85-117, 2015.

3. [3] Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, no. 7553, pp. 436-444, 2015.

4. [4] Y. LeCun et al., “Gradient-based learning applied to document recognition,” Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2323, 1998.

5. [5] R. Salakhutdinov and G.E. Hinton, “Deep Boltzmann machines,” International Conference on Artificial Intelligence and Statics, no. 3, pp. 448-455, 2009.

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