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Volumn , Issue , 2004, Pages 138-145

Semi-supervised mixture-of-experts classification

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION FILTERING; MIXTURE MODELING TECHNIQUES; MIXTURE-OF-EXPERTS (MOE) MODEL; PARAMETER VECTORS;

EID: 19544362182     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2004.10103     Document Type: Conference Paper
Times cited : (12)

References (15)
  • 6
    • 0012999549 scopus 로고
    • Technical Report 108, MIT Center for Biological and Computational Learning, December
    • Ghahramani, Z. and M.I. Jordan, Learning from incomplete data, Technical Report 108, MIT Center for Biological and Computational Learning, December 1994.
    • (1994) Learning from Incomplete Data
    • Ghahramani, Z.1    Jordan, M.I.2
  • 7
    • 0000125534 scopus 로고
    • Sample selection bias as a specification error
    • J. Heckman, "Sample selection bias as a specification error", Econometrica, 1979, pp. 153-161.
    • (1979) Econometrica , pp. 153-161
    • Heckman, J.1
  • 8
    • 0001691634 scopus 로고    scopus 로고
    • Bias/variance decompositions for likelihood-based estimators
    • T. Heskes, "Bias/variance decompositions for likelihood-based estimators", Neural Computation, 1998, pp. 1425-1433.
    • (1998) Neural Computation , pp. 1425-1433
    • Heskes, T.1
  • 12
    • 84898980291 scopus 로고    scopus 로고
    • A mixture of experts classifier with learning based on both labelled and unlabelled data
    • MIT Press
    • D. Miller and S. Uyar. "A mixture of experts classifier with learning based on both labelled and unlabelled data", Advances in Neural Information Processing Systems 9, MIT Press, 1997, pp. 571-578.
    • (1997) Advances in Neural Information Processing Systems , vol.9 , pp. 571-578
    • Miller, D.1    Uyar, S.2
  • 13
    • 0033886806 scopus 로고    scopus 로고
    • Text classification from labeled and unlabeled documents using EM
    • K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell, "Text classification from labeled and unlabeled documents using EM", Machine Learning, 2000, pp. 103-134.
    • (2000) Machine Learning , pp. 103-134
    • Nigam, K.1    McCallum, A.K.2    Thrun, S.3    Mitchell, T.M.4
  • 14
    • 0028499630 scopus 로고
    • The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon
    • B. Shahshahani and D. Landgrebe, "The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon", IEEE Transactions on Geoscience and Remote Sensing, 1994, pp. 1087-1095.
    • (1994) IEEE Transactions on Geoscience and Remote Sensing , pp. 1087-1095
    • Shahshahani, B.1    Landgrebe, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.