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Volumn , Issue , 2012, Pages 584-593

Unsupervised joint alignment and clustering using bayesian nonparametrics

Author keywords

[No Author keywords available]

Indexed keywords

ALIGNMENT ALGORITHMS; BAYESIAN NONPARAMETRICS; COMPLEX DATASETS; CONTINUOUS PARAMETERS; DIRICHLET PROCESS; LEARNING SCHEMES; MULTIPLE MODALITIES; TRANSFORMATION FUNCTIONS;

EID: 84886007762     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (10)

References (33)
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    • Blackwell, D.1    MacQueen, J.2
  • 3
    • 84867186048 scopus 로고    scopus 로고
    • Variational inference for dirichlet process mixtures
    • D. M. Blei and M. I. Jordan. Variational inference for Dirichlet process mixtures. Journal of Bayesian Analysis, 1(1):121-144, 2006.
    • (2006) Journal of Bayesian Analysis , vol.1 , Issue.1 , pp. 121-144
    • Blei, D.M.1    Jordan, M.I.2
  • 4
    • 0002205556 scopus 로고    scopus 로고
    • Rao-blackwellization of sampling schemes
    • G. Cassella and C. P. Robert. Rao-Blackwellization of sampling schemes. Biometrika, 83(1):81-94, 1996.
    • (1996) Biometrika , vol.83 , Issue.1 , pp. 81-94
    • Cassella, G.1    Robert, C.P.2
  • 10
    • 84950937290 scopus 로고
    • Bayesian density estimation and inference using mixtures
    • June
    • M. D. Escobar and M. West. Bayesian density estimation and inference using mixtures. Journal of the American Statistical Association, 90(430):577-588, June 1995.
    • (1995) Journal of the American Statistical Association , vol.90 , Issue.430 , pp. 577-588
    • Escobar, M.D.1    West, M.2
  • 19
    • 33745170376 scopus 로고    scopus 로고
    • Segmental hidden markov models with random effects for waveform modeling
    • S. Kim and P. Smyth. Segmental hidden Markov models with random effects for waveform modeling. Journal ofMachine Learning Research, 7:945-969, 2006.
    • (2006) Journal OfMachine Learning Research , vol.7 , pp. 945-969
    • Kim, S.1    Smyth, P.2
  • 27
    • 0002788893 scopus 로고    scopus 로고
    • A view of the em algorithm that justifies incremental, sparse, and other variants
    • R. M. Neal and G. E. Hinton. A view of the EM algorithm that justifies incremental, sparse, and other variants. In Learning in Graphical Models, pages 355-368, 1998.
    • (1998) Learning in Graphical Models , pp. 355-368
    • Neal, R.M.1    Hinton, G.E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.