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Volumn , Issue , 2017, Pages 2422-2428

Unsupervised large graph embedding

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; SPECTRUM ANALYSIS; STOCHASTIC SYSTEMS;

EID: 85028549826     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (153)

References (25)
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    • Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction
    • Nie, F.; Xu, D.; Tsang, I. W.; and Zhang, C. 2010. Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction. IEEE Transactions on Image Processing 19(7):1921-1932.
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    • Nie, F.1    Xu, D.2    Tsang, I.W.3    Zhang, C.4
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    • Nie, F.; Xu, D.; Li, X.; and Xiang, S. 2011. Semisupervised dimensionality reduction and classification through virtual label regression. IEEE Trans. Systems, Man, and Cybernetics, Part B 41(3):675-685.
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    • Nie, F.1    Xu, D.2    Li, X.3    Xiang, S.4
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    • LSQR: An algorithm for sparse linear equations and sparse least squares
    • Paige, C. C., and Saunders, M. A. 1982. LSQR: an algorithm for sparse linear equations and sparse least squares. ACM Trans. Math. Softw. 8(1):43-71.
    • (1982) ACM Trans. Math. Softw , vol.8 , Issue.1 , pp. 43-71
    • Paige, C.C.1    Saunders, M.A.2
  • 17
    • 0035015680 scopus 로고    scopus 로고
    • Three learning phases for radial-basis-function networks
    • Schwenker, F.; Kestler, H. A.; and Palm, G. 2001. Three learning phases for radial-basis-function networks. Neural Networks 14(4-5):439-458.
    • (2001) Neural Networks , vol.14 , Issue.4-5 , pp. 439-458
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  • 18
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    • T, R. S., and K, S. L. 2000. Nonlinear dimensionality reduction by locally linear embedding. Science 290(5):2323-2326.
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    • Graph embedding and extensions: A general framework for dimensionality reduction
    • Yan, S.; Xu, D.; Zhang, B.; Zhang, H.; Yang, Q.; and Lin, S. 2007. Graph embedding and extensions: A general framework for dimensionality reduction. IEEE Trans. Pattern Anal. Mach. Intell. 29(1):40-51.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.