An entropic estimator for structure discovery

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 723-729

  Brand, Matthew ^a  

^a MITSUBISHI ELECTRIC RESEARCH LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENTROPY; ESTIMATION; HIDDEN MARKOV MODELS; UNCERTAINTY ANALYSIS;

CONDITIONAL PROBABILITIES; DESCRIPTIVE STATISTICS; HIDDEN MARKOV MODELS (HMMS); HIGHLY-CORRELATED; ITERATIVE ESTIMATION; MAXIMUM A POSTERIORI; PARAMETER LEARNING; POSTERIOR PROBABILITY;

PARAMETER ESTIMATION;

EID: 0000148207     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

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2. Brand, M. (1998). Pattern discovery via entropy minimization. To appear in Proc, Artificial Intelligence and Statistics #7.
3. Merz, C. and Murphy, P. (1998). UCI repository of machine learning databases.
4. Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2): 257-286.
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6. Rissanen, J. (1989). Stochastic Complexity and Statistical Inquiry, World Scientific.
7. Stolcke, A. and Omohundro, S. (1994). Best-first model merging for hidden Markov model induction. TR-94-003, International Computer Science Institute, U.C. Berkeley.
8. Takami, J.-I. and Sagayama, S. (1991). Automatic generation of the hidden Markov model by successive state splitting on the contextual domain and the temporal domain. TR SP91-88, IEICE.
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10. Wolfertstetter, F. and Ruske, G. (1995). Structured Markov models for speech recognition. In International Conference on Acoustics, Speech, and Signal Processing, Volume 1, pages 544-7.