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Volumn , Issue , 2007, Pages

Integrating global and local structures: A least squares framework for dimensionality reduction

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DISCRIMINANT ANALYSIS; MATHEMATICAL MODELS;

EID: 35148833127     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2007.383040     Document Type: Conference Paper
Times cited : (77)

References (25)
  • 2
    • 0043278893 scopus 로고    scopus 로고
    • Laplacian eigenmaps and sepctral techniques for embedding and clustering
    • M. Belkin and P. Niyogi. Laplacian eigenmaps and sepctral techniques for embedding and clustering. In Advances in Neural Information Processing Systems, volume 15, 2001. 1, 3
    • (2001) Advances in Neural Information Processing Systems , vol.15 , Issue.1 , pp. 3
    • Belkin, M.1    Niyogi, P.2
  • 3
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from examples
    • 7
    • M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: a geometric framework for learning from examples. Journal of Machine Learning Research, 7:2399-2434, 2006. 1, 6
    • (2006) Journal of Machine Learning Research , vol.2399-2434 , Issue.1 , pp. 6
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 5
  • 6
    • 35148866030 scopus 로고    scopus 로고
    • V. de Silva and J. Tenenbaum. Global versus local methods in nonlinear dimensionality reduction. In Advances in Neural Information Processing Systems, pages 705-712, 2002. 1
    • V. de Silva and J. Tenenbaum. Global versus local methods in nonlinear dimensionality reduction. In Advances in Neural Information Processing Systems, pages 705-712, 2002. 1
  • 8
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • 97457
    • S. Dudoit, J. Fridlyand, and T. P. Speed. Comparison of discrimination methods for the classification of tumors using gene expression data. Journal of the American Statistical Association, 97(457):77-87, 2002. 1
    • (2002) Journal of the American Statistical Association , vol.77-87 , pp. 1
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 9
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • R. Fisher. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7:179-188, 1936. 1
    • (1936) Annals of Eugenics , vol.7 , Issue.179-188 , pp. 1
    • Fisher, R.1
  • 11
    • 0004236492 scopus 로고    scopus 로고
    • The Johns Hopkins University Press, Baltimore, MD, USA, third edition
    • G. H. Golub and C. F. Van Loan. Matrix Computations. The Johns Hopkins University Press, Baltimore, MD, USA, third edition, 1996. 2, 3
    • (1996) Matrix Computations , vol.2 , pp. 3
    • Golub, G.H.1    Van Loan, C.F.2
  • 15
    • 21844512674 scopus 로고
    • Discriminant analysis with singular covariance matrices: Methods and applications to spectroscopic data
    • W. Krzanowski, P. Jonathan, W. McCarthy, and M. Thomas. Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data. Applied Statistics, 44:101-115, 1995. 1
    • (1995) Applied Statistics , vol.44 , Issue.101-115 , pp. 1
    • Krzanowski, W.1    Jonathan, P.2    McCarthy, W.3    Thomas, M.4
  • 18
    • 0003235939 scopus 로고    scopus 로고
    • Statistical learning theory
    • V. Vapnik. Statistical learning theory. Wiley, New York, 1998. 1
    • (1998) Wiley, New York , pp. 1
    • Vapnik, V.1
  • 20
    • 25144481906 scopus 로고    scopus 로고
    • Semi-supervised protein classification using cluster kernels
    • 2115
    • W Weston, C. Leslie, E. Ie, D. Zhou, A. Elisseeff, and W. Noble. Semi-supervised protein classification using cluster kernels. Bioinformatics, 21(15):3241-3247, 2005. 6
    • (2005) Bioinformatics , vol.3241-3247 , pp. 6
    • Weston, W.1    Leslie, C.2    Ie, E.3    Zhou, D.4    Elisseeff, A.5    Noble, W.6
  • 21
    • 21844447839 scopus 로고    scopus 로고
    • J. Ye. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. Journal of Machine Learning Research, 6:483-502, 2005. 1, 2, 4
    • J. Ye. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. Journal of Machine Learning Research, 6:483-502, 2005. 1, 2, 4
  • 23
    • 33745743918 scopus 로고    scopus 로고
    • Computational and theoretical analysis of null space and orthogonal linear discriminant analysis
    • 7
    • J. Ye and T. Xiong. Computational and theoretical analysis of null space and orthogonal linear discriminant analysis. Journal of Machine Learning Research, 7:1183-1204, 2006. 4
    • (2006) Journal of Machine Learning Research , vol.1183-1204 , pp. 4
    • Ye, J.1    Xiong, T.2
  • 24
    • 35148859643 scopus 로고    scopus 로고
    • D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Schölkopf. Learning with local and global consistency. In Advances in Neural Information Processing Systems, pages 321-328, 2003. 6
    • D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Schölkopf. Learning with local and global consistency. In Advances in Neural Information Processing Systems, pages 321-328, 2003. 6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.