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Volumn , Issue , 2009, Pages 777-784

Nonparametric factor analysis with beta process priors

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; CELL LINES; CONJUGATE PRIOR; DATA SETS; DIRICHLET PROCESS; FACTOR ANALYSIS; INFERENCE ALGORITHM; LINEAR COMBINATIONS; NON-PARAMETRIC; PROCESS FACTOR; SPARSE SET; VARIATIONAL BAYES;

EID: 71149088102     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (210)

References (18)
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    • Beal, M. (2003). Variational algorithms for approximate bayesian inference. Doctoral dissertation, Gatsby Computational Neuroscience Unit, University College London.
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    • Beal, M.1
  • 4
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    • A bayesian analysis of some nonparametric problems
    • Ferguson, T. (1973). A bayesian analysis of some nonparametric problems. The Annals of Statistics, 1:209-230.
    • (1973) The Annals of Statistics , vol.1 , pp. 209-230
    • Ferguson, T.1
  • 6
    • 0001241617 scopus 로고
    • Nonparametric bayes estimators based on beta processes in models for life history data
    • Hjort, N. L. (1990). Nonparametric bayes estimators based on beta processes in models for life history data. Annals of Statistics, 18:3, 1259-1294.
    • (1990) Annals of Statistics , vol.18 , Issue.3 , pp. 1259-1294
    • Hjort, N.L.1
  • 9
    • 70049117757 scopus 로고    scopus 로고
    • A stick-breaking construction of the beta process
    • Duke University
    • Paisley, J., & Carin, L. (2009). A stick-breaking construction of the beta process (Technical Report). Duke University, ee.duke.edu/~jwp4/ StickBP.pdf.
    • (2009) Technical Report
    • Paisley, J.1    Carin, L.2
  • 12
    • 0000720609 scopus 로고
    • A constructive definition of dirichlet priors
    • Sethuraman, J. (1994). A constructive definition of dirichlet priors. Statistica Sinica, 4:639-650.
    • (1994) Statistica Sinica , vol.4 , pp. 639-650
    • Sethuraman, J.1
  • 13
    • 56449122300 scopus 로고    scopus 로고
    • Proceedings of the 25th International Conference on Machine Learning
    • mstruct:, pp. 952-959
    • Shringarpure, S., & Xing, E. P. (2008). mstruct: A new admixture model for inference of population structure in light of both genetic admixing and allele mutation. Proceedings of the 25th International Conference on Machine Learning (pp. 952-959).
    • (2008)
    • Shringarpure, S.1    Xing, E.P.2
  • 17
    • 0001224048 scopus 로고    scopus 로고
    • Sparse bayesian learning and the relevance vector machine
    • Tipping, M. E. (2001). Sparse bayesian learning and the relevance vector machine. The Journal of Machine Learning Research, 1:211-244.
    • (2001) The Journal of Machine Learning Research , vol.1 , pp. 211-244
    • Tipping, M.E.1
  • 18
    • 0242295767 scopus 로고    scopus 로고
    • Bayesian factor regression models in the "large p, small n" paradigm
    • West, M. (2003). Bayesian factor regression models in the "large p, small n" paradigm. Bayesian Statistics, 7, 723-732.
    • (2003) Bayesian Statistics , vol.7 , pp. 723-732
    • West, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.