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Volumn , Issue , 2010, Pages 87-94

Distance dependent Chinese restaurant processes

Author keywords

[No Author keywords available]

Indexed keywords

ACROSS TIME; BAYESIAN; CLUSTERING MODEL; GIBBS SAMPLERS; GIBBS SAMPLING; MIXTURE MODEL; MODEL DEPENDENCIES; NON-PARAMETRIC; SEQUENTIAL DATA; TEXT CORPORA; TIME-DEPENDENT MODELS;

EID: 77956498383     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (32)

References (16)
  • 1
    • 52649163923 scopus 로고    scopus 로고
    • Dynamic non-parametric mixture models and the recurrent Chinese restaurant process with applications to evolutionary clustering
    • Ahmed, A. and Xing, E. Dynamic non-parametric mixture models and the recurrent Chinese restaurant process with applications to evolutionary clustering. In International Conference on Data Mining, 2008.
    • (2008) International Conference on Data Mining
    • Ahmed, A.1    Xing, E.2
  • 4
    • 37549057387 scopus 로고    scopus 로고
    • Generalized spatial Dirichlet process models
    • Duan, J., Guindani, M., and Gelfand, A. Generalized spatial Dirichlet process models. Biometrika, 94:809-825, 2007.
    • (2007) Biometrika , vol.94 , pp. 809-825
    • Duan, J.1    Guindani, M.2    Gelfand, A.3
  • 7
    • 67349214856 scopus 로고    scopus 로고
    • Adaptor grammars: A framework for specifying compositional nonparametric Bayesian models
    • Schölkopf, B. Piatt, J. and Hoffman, T. (eds.), Cambridge, MA, MIT Press
    • Johnson, M., Griffiths, T., and S., Goldwater. Adaptor grammars: A framework for specifying compositional nonparametric Bayesian models. In Schölkopf, B., Piatt, J., and Hoffman, T. (eds.), Advances in Neural Information Processing Systems 19, pp. 641-648, Cambridge, MA, 2007. MIT Press.
    • (2007) Advances in Neural Information Processing Systems , vol.19 , pp. 641-648
    • Johnson, M.1    Griffiths, T.2    Goldwater, S.3
  • 10
    • 0000736067 scopus 로고    scopus 로고
    • Simulating normalizing constants: From importance sampling to bridge sampling to path sampling
    • Meng, X. and Gelman, A. Simulating normalizing constants: From importance sampling to bridge sampling to path sampling. Statistical Science, 13(2): 163-185, 1998.
    • (1998) Statistical Science , vol.13 , Issue.2 , pp. 163-185
    • Meng, X.1    Gelman, A.2
  • 11
    • 77950032550 scopus 로고    scopus 로고
    • Markov chain sampling methods for Dirichlet process mixture models
    • Neal, R. Markov chain sampling methods for Dirichlet process mixture models. Journal of Computational and Graphical Statistics, 9(2):249-265, 2000.
    • (2000) Journal of Computational and Graphical Statistics , vol.9 , Issue.2 , pp. 249-265
    • Neal, R.1
  • 12
    • 0242641721 scopus 로고    scopus 로고
    • Lecture Notes for St. Flour Summer School. Springer-Verlag, New York, NY
    • Pitman, J. Combinatorial Stochastic Processes. Lecture Notes for St. Flour Summer School. Springer-Verlag, New York, NY, 2002.
    • (2002) Combinatorial Stochastic Processes
    • Pitman, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.