Equivalence of Linear Boltzmann Chains and Hidden Markov Models

Neural Computation

Volumn 8, Issue 1, 1996, Pages 178-181

  MacKay, David J C ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 2342533081     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/neco.1996.8.1.178     Document Type: Article

References (5)

1. Luttrell, S. P. 1989. The Gibbs Machine Applied to Hidden Markov Model Problems. Part 1: Basic Theory, Tech. Rep. 99, SP4 division, RSRE, Malvern, U.K.
2. Saul, L., and Jordan, M. 1995. Boltzmann chains and hidden Markov models. Adv. Neural Inform. Process. Syst. 7, 435-442.
3. Seneta, E. 1973. Non-Negative Matrices. John Wiley & Sons, New York.
4. Williams, C. K. I. 1990. Using deterministic Boltzmann machines to discriminate temporally distorted strings. Master's thesis, Department of Computer Science, University of Toronto; see also Williams, C. K. I., and Hinton, G. E. 1990. Mean field networks that learn to discriminate temporally distorted strings. In Proceedings of the 1990 Connectionist Models Summer School, D. S. Touretzky, J. L. Elman, T. S. Sejnowski, and G. E. Hinton, eds. Morgan Kaufmann, San Mateo, CA.
5. Williams, C. K. I. 1990. Using deterministic Boltzmann machines to discriminate temporally distorted strings. Master's thesis, Department of Computer Science, University of Toronto; see also Williams, C. K. I., and Hinton, G. E. 1990. Mean field networks that learn to discriminate temporally distorted strings. In Proceedings of the 1990 Connectionist Models Summer School, D. S. Touretzky, J. L. Elman, T. S. Sejnowski, and G. E. Hinton, eds. Morgan Kaufmann, San Mateo, CA.