메뉴 건너뛰기




Volumn 10, Issue 3, 2002, Pages 201-219

A Bayesian approach for structural learning with hidden Markov models

Author keywords

[No Author keywords available]

Indexed keywords

MARKOV PROCESSES; MATHEMATICAL MODELS; PARAMETER ESTIMATION; SPEECH RECOGNITION;

EID: 0036455515     PISSN: 10589244     EISSN: None     Source Type: Journal    
DOI: 10.1155/2002/604791     Document Type: Article
Times cited : (11)

References (33)
  • 2
    • 0035002807 scopus 로고    scopus 로고
    • Evaluation of gene-finding programs on mammalian sequences
    • S. Rogic, A.K. Mackworth and F.B.F. Ouellette, Evaluation of gene-finding programs on mammalian sequences, Genomic Research 11 (2001), 817-832.
    • (2001) Genomic Research , vol.11 , pp. 817-832
    • Rogic, S.1    Mackworth, A.K.2    Ouellette, F.B.F.3
  • 3
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Feb.
    • L.R. Rabiner, A tutorial on hidden markov models and selected applications in speech recognition, Proceedings of the IEEE 77(2) (Feb. 1989), 257-285.
    • (1989) Proceedings of the IEEE , vol.77 , Issue.2 , pp. 257-285
    • Rabiner, L.R.1
  • 5
    • 0001012402 scopus 로고    scopus 로고
    • Bayesian temporal data clustering using hidden Markov model representation
    • P. Langley, ed., Morgan Kaufmann Publishers
    • C. Li and G. Biswas, Bayesian temporal data clustering using hidden markov model representation, in: Proceedings of the 17th International conference on Machine Learning. P. Langley, ed., Morgan Kaufmann Publishers, 2000, pp. 543-550.
    • (2000) Proceedings of the 17th International conference on Machine Learning , pp. 543-550
    • Li, C.1    Biswas, G.2
  • 7
    • 84899029607 scopus 로고    scopus 로고
    • Training algorithms for hidden Markov models using entropy based distance functions
    • Y. Singer and M. Warmuth, Training algorithms for hidden markov models using entropy based distance functions, Advances in Neural Information Processing Systems 9 (1996), 641-647.
    • (1996) Advances in Neural Information Processing Systems , vol.9 , pp. 641-647
    • Singer, Y.1    Warmuth, M.2
  • 8
    • 0030216671 scopus 로고    scopus 로고
    • Training approaches for hidden Markov models
    • S. Kwong, Q.H. He and K.F. Man, Training approaches for hidden markov models, Electronics Letters 32(17) (1996), 1554-1555.
    • (1996) Electronics Letters , vol.32 , Issue.17 , pp. 1554-1555
    • Kwong, S.1    He, Q.H.2    Man, K.F.3
  • 9
    • 0000353178 scopus 로고
    • A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains
    • L.E. Baum, T. Petrie, G. Soules and N. Weiss, A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains, The Annuals of Mathematical Statistics 4(1) (1970), 164-171.
    • (1970) The Annuals of Mathematical Statistics , vol.4 , Issue.1 , pp. 164-171
    • Baum, L.E.1    Petrie, T.2    Soules, G.3    Weiss, N.4
  • 11
    • 0031268341 scopus 로고    scopus 로고
    • Factorial hidden Markov models
    • Z. Ghahramani and M.I. Jordan, Factorial hidden markov models, Machine Leaning 29 (1997), 245-273.
    • (1997) Machine Leaning , vol.29 , pp. 245-273
    • Ghahramani, Z.1    Jordan, M.I.2
  • 12
    • 0003615076 scopus 로고
    • Tech. Rep. TR-94-003, International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, Jan.
    • A. Stolcke and S.M. Omohundro, Best-first model merging for hidden markov model induction, Tech. Rep. TR-94-003, International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, Jan. 1994.
    • (1994) Best-first model merging for hidden markov model induction
    • Stolcke, A.1    Omohundro, S.M.2
  • 14
    • 0000675167 scopus 로고    scopus 로고
    • Structure learning in conditional probability models via an entropic prior and parameter extinction
    • M. Brand, Structure learning in conditional probability models via an entropic prior and parameter extinction, Neural Computation 11 (1999), 1155-1182.
    • (1999) Neural Computation , vol.11 , pp. 1155-1182
    • Brand, M.1
  • 16
    • 0030715097 scopus 로고    scopus 로고
    • Hmm topology design using maximum likelihood successive state splitting
    • M. Ostendorf and H. Singer, Hmm topology design using maximum likelihood successive state splitting, Computer Speech and Language 11 (1997), 17-41.
    • (1997) Computer Speech and Language , vol.11 , pp. 17-41
    • Ostendorf, M.1    Singer, H.2
  • 18
    • 0000698534 scopus 로고    scopus 로고
    • Variational inference for bayesian mixtures of factor analysers
    • S.A. Solla, T.K. Leen and K.R. Muller, eds, MIT press, Cambridge, MA
    • Z. Ghahramani and M.J. Beal, Variational inference for bayesian mixtures of factor analysers, in: Advances in Neural Information Processing Systems, (Vol. 12), S.A. Solla, T.K. Leen and K.R. Muller, eds, MIT press, Cambridge, MA, 1999.
    • (1999) Advances in Neural Information Processing Systems , vol.12
    • Ghahramani, Z.1    Beal, M.J.2
  • 19
    • 84898964031 scopus 로고    scopus 로고
    • A variational bayesian framework for graphical models
    • T. et al. Leen, ed., MIT press, Cambridge, MA
    • H. Attias, A variational bayesian framework for graphical models, in: Advances in Neural Information Processing Systems, T. et al. Leen, ed., MIT press, Cambridge, MA, 2000.
    • (2000) Advances in Neural Information Processing Systems
    • Attias, H.1
  • 21
    • 34249832377 scopus 로고
    • A bayesian method for the induction of probabilistic network from data
    • G.F. Cooper and E. Herskovits, A bayesian method for the induction of probabilistic network from data, Machine Learning 9 (1992), 309-347.
    • (1992) Machine Learning , vol.9 , pp. 309-347
    • Cooper, G.F.1    Herskovits, E.2
  • 24
    • 84937730674 scopus 로고
    • Explaining the gibbs sampler
    • Aug.
    • G. Casella and E.I. George, Explaining the gibbs sampler, The American Statistician 46(3) (Aug. 1992), 167-174.
    • (1992) The American Statistician , vol.46 , Issue.3 , pp. 167-174
    • Casella, G.1    George, E.I.2
  • 25
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • G. Schwarz, Estimating the dimension of a model, Annuals of Statistics 6 (1978), 461-464.
    • (1978) Annuals of Statistics , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 26
    • 0002607026 scopus 로고    scopus 로고
    • Bayesian classification(autoclass): Theory and results
    • (Chapter 6), U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth and R. Uthurusamy, eds, AAAI-MIT press
    • P. Cheeseman and J. Stutz, Bayesian classification(autoclass): Theory and results, in: Advances in Knowledge Discovery and Data Mining, (Chapter 6), U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth and R. Uthurusamy, eds, AAAI-MIT press, 1996, pp. 153-180.
    • (1996) Advances in Knowledge Discovery and Data Mining , pp. 153-180
    • Cheeseman, P.1    Stutz, J.2
  • 27
    • 0001098776 scopus 로고
    • A universal prior for integers and estimation by minimum description length
    • J. Rissanen, A universal prior for integers and estimation by minimum description length, Annual of Statistics 11 (1983), 416-431.
    • (1983) Annual of Statistics , vol.11 , pp. 416-431
    • Rissanen, J.1
  • 29
    • 0031272327 scopus 로고    scopus 로고
    • Efficient approximations for the marginal likelihood of bayesian networks with hidden variables
    • D.M. Chickering and D. Heckerman, Efficient approximations for the marginal likelihood of bayesian networks with hidden variables, Machine Learning 29 (1997), 181-212.
    • (1997) Machine Learning , vol.29 , pp. 181-212
    • Chickering, D.M.1    Heckerman, D.2
  • 32
    • 63249112814 scopus 로고
    • Dimensionality and sample size considerations in pattern recognition practice
    • P.R. Krishnaiah and L.N. Kanal, eds, North-Holland Publishing Company, Amsterdam
    • A.N. Jain and B. Chandrasekaran, Dimensionality and sample size considerations in pattern recognition practice, in: Handbook of statistics, P.R. Krishnaiah and L.N. Kanal, eds, North-Holland Publishing Company, Amsterdam, 1982, pp. 835-855.
    • (1982) Handbook of statistics , pp. 835-855
    • Jain, A.N.1    Chandrasekaran, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.