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Volumn 2006, Issue , 2006, Pages 3399-3404

Feature representation based on intrinsic structure discovery in high dimensional space

Author keywords

[No Author keywords available]

Indexed keywords

BANDPASS FILTERS; EMBEDDED SYSTEMS; IMAGING SYSTEMS; INFORMATION ANALYSIS; LEARNING ALGORITHMS; TRACKING (POSITION);

EID: 33845675870     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2006.1642221     Document Type: Conference Paper
Times cited : (10)

References (12)
  • 3
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • December
    • S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, pp. 2323-2326, December 2000.
    • (2000) Science , vol.290 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 5
    • 0003825410 scopus 로고    scopus 로고
    • Monographs on Statistics and Applied Probability 88, CRC Press, 2nd ed., September
    • T. F. Cox and M. A. A. Cox, Multidimensional Scaling. Monographs on Statistics and Applied Probability 88, CRC Press, 2nd ed., September 2000.
    • (2000) Multidimensional Scaling
    • Cox, T.F.1    Cox, M.A.A.2
  • 6
    • 0034704189 scopus 로고    scopus 로고
    • The manifold ways of perception
    • December
    • H. S. Seung and D. D. Lee, "The manifold ways of perception," Science, vol. 290, pp. 2268-2269, December 2000.
    • (2000) Science , vol.290 , pp. 2268-2269
    • Seung, H.S.1    Lee, D.D.2
  • 7
    • 0034704229 scopus 로고    scopus 로고
    • A gloabal geometric framework for nonlinear dimensionality reduction
    • December
    • J. B. Tenenbaum, V. de Silva, and J. C. Langford, "A gloabal geometric framework for nonlinear dimensionality reduction," Science, vol. 290, pp. 2319-2323, December 2000. http://isomap.stanford.edu/datasets.html.
    • (2000) Science , vol.290 , pp. 2319-2323
    • Tenenbaum, J.B.1    De Silva, V.2    Langford, J.C.3
  • 8
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Computation, vol. 15, no. 6, pp. 1373-1396, 2003.
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 9
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: Unsupervised learning of low dimensional manifolds
    • June
    • S. T. Roweis and L. K. Saul, "Think globally, fit locally: Unsupervised learning of low dimensional manifolds.," Journal of Machine Learning Research, vol. 4, pp. 119-155, June 2003.
    • (2003) Journal of Machine Learning Research , vol.4 , pp. 119-155
    • Roweis, S.T.1    Saul, L.K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.