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Volumn 1, Issue , 2010, Pages 512-517

Gaussian Mixture Model with local consistency

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; IMAGE SEGMENTATION; LARGE SCALE SYSTEMS; MAXIMUM PRINCIPLE;

EID: 77958546380     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (55)

References (19)
  • 2
    • 33750729556 scopus 로고    scopus 로고
    • Manifold reg-ularization: A geometric framework for learning from examples
    • Belkin, M.; Niyogi, P.; and Sindhwani, V. 2006. Manifold reg-ularization: A geometric framework for learning from examples. Journal of Machine Learning Research 7:2399-2434.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 7
    • 70049103855 scopus 로고    scopus 로고
    • Probabilistic dyadic data analysis with local and global consistency
    • Cai, D.; Wang, X.; and He, X. 2009. Probabilistic dyadic data analysis with local and global consistency. In ICML'09.
    • (2009) ICML'09
    • Cai, D.1    Wang, X.2    He, X.3
  • 13
    • 0038363049 scopus 로고
    • North Holland, Budapest: Akadémiai Kiadó
    • Lovasz, L., and Plummer, M. 1986. Matching Theory. North Holland, Budapest: Akadémiai Kiadó.
    • (1986) Matching Theory
    • Lovasz, L.1    Plummer, M.2
  • 15
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Roweis, S., and Saul, L. 2000. Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500):2323-2326.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.1    Saul, L.2
  • 17
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • Tenenbaum, J.; de Silva, V.; and Langford, J. 2000. A global geometric framework for nonlinear dimensionality reduction. Science 290(5500):2319-2323.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2319-2323
    • Tenenbaum, J.1    De Silva, V.2    Langford, J.3
  • 19
    • 31844438481 scopus 로고    scopus 로고
    • Harmonic mixtures: Combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
    • Zhu, X., and Lafferty, J. 2005. Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning. In ICML '05: Proceedings of the 22nd international conference on Machine learning, 1052-1059.
    • (2005) ICML '05: Proceedings of the 22nd International Conference on Machine Learning , pp. 1052-1059
    • Zhu, X.1    Lafferty, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.