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Volumn , Issue , 2004, Pages 775-782

Automated hierarchical mixtures of probabilistic principal component analyzers

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA REDUCTION; HIERARCHICAL SYSTEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY DISTRIBUTIONS;

EID: 14344262272     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (25)
  • 1
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723.
    • (1974) IEEE Transactions on Automatic Control , vol.19 , pp. 716-723
    • Akaike, H.1
  • 8
    • 0002878444 scopus 로고    scopus 로고
    • Feature subset selection and order identification for unsupervised learning
    • Morgan Kaufmann, San Francisco, CA
    • Dy, J. G., & Brodley, C. E. (2000). Feature subset selection and order identification for unsupervised learning. Proceedings of the 17th International Conf. on Machine Learning (pp. 247-254). Morgan Kaufmann, San Francisco, CA.
    • (2000) Proceedings of the 17th International Conf. on Machine Learning , pp. 247-254
    • Dy, J.G.1    Brodley, C.E.2
  • 10
    • 0032269108 scopus 로고    scopus 로고
    • How many clusters? which clustering method? - Answers via model-based cluster analysis
    • Fraley, C., & Raftery, A. (1998). How many clusters? which clustering method? - answers via model-based cluster analysis. The Computer Journal, 41, 578-588.
    • (1998) The Computer Journal , vol.41 , pp. 578-588
    • Fraley, C.1    Raftery, A.2
  • 16
    • 0043164386 scopus 로고    scopus 로고
    • Automatic choice of dimensionality for PCA
    • Minka, T. P. (2000). Automatic choice of dimensionality for PCA. NIPS (pp. 598-604).
    • (2000) NIPS , pp. 598-604
    • Minka, T.P.1
  • 20
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461-464.
    • (1978) The Annals of Statistics , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 21
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining multiple partitions
    • Strehl, A., & Ghosh, J. (2002). Cluster ensembles - a knowledge reuse framework for combining multiple partitions. Journal on Machine Learning Research, 3, 583-617.
    • (2002) Journal on Machine Learning Research , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 22
    • 0036565797 scopus 로고    scopus 로고
    • Hierarchical GTM: Constructing localized nonlinear projection manifolds in a principled way
    • Tino, P., & Nabney, I. (2002). Hierarchical GTM: Constructing localized nonlinear projection manifolds in a principled way. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 639-656.
    • (2002) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.24 , pp. 639-656
    • Tino, P.1    Nabney, I.2
  • 23
    • 0033556788 scopus 로고    scopus 로고
    • Mixtures of probabilistic principal component analysers
    • Tipping, M., & Bishop, C. (1999a). Mixtures of probabilistic principal component analysers. Neural Computation, 11, 443-482.
    • (1999) Neural Computation , vol.11 , pp. 443-482
    • Tipping, M.1    Bishop, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.