메뉴 건너뛰기




Volumn 30, Issue 9, 2008, Pages 1547-1556

Out-of-sample extrapolation of learned manifolds

Author keywords

Manifold learning; Maximum Variance Unfolding; Out of sample extrapolation

Indexed keywords

TRELLIS CODES;

EID: 48049090960     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.70813     Document Type: Article
Times cited : (41)

References (17)
  • 2
    • 33750733400 scopus 로고    scopus 로고
    • Spectral Methods for Dimensionality Reduction
    • O. Chapelle, B. Schölkopf, and A. Zien, eds. MIT Press
    • L. Saul, K. Weinberger, F. Sha, J. Ham, and D. Lee, "Spectral Methods for Dimensionality Reduction," Semisupervised Learning, O. Chapelle, B. Schölkopf, and A. Zien, eds. MIT Press, 2006.
    • (2006) Semisupervised Learning
    • Saul, L.1    Weinberger, K.2    Sha, F.3    Ham, J.4    Lee, D.5
  • 3
    • 33744949513 scopus 로고    scopus 로고
    • Unsupervised Learning of Image Manifolds by Semidefinite Programming
    • K. Weinberger and L. Saul, "Unsupervised Learning of Image Manifolds by Semidefinite Programming," Int'l J. Computer Vision, vol. 70, no. 1, pp. 77-90, 2006.
    • (2006) Int'l J. Computer Vision , vol.70 , Issue.1 , pp. 77-90
    • Weinberger, K.1    Saul, L.2
  • 6
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear Component Analysis as a Kernel Eigenvalue Problem
    • B. Schölkopf, A. Smola, and K.-R. Müller, "Nonlinear Component Analysis as a Kernel Eigenvalue Problem, Neural Computation, vol. 10, pp. 1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3
  • 7
    • 84899009769 scopus 로고    scopus 로고
    • V. de Silva and J. Tenenbaum, Global versus Local Methods in Nonlinear Dimensionality Reduction, Proc. Advances in Neural Information Processing Systems, pp. 705-712, 2003.
    • V. de Silva and J. Tenenbaum, "Global versus Local Methods in Nonlinear Dimensionality Reduction," Proc. Advances in Neural Information Processing Systems, pp. 705-712, 2003.
  • 12
    • 2342517502 scopus 로고    scopus 로고
    • Think Globally, Fit Locally: Unsupervised Learning of Low-Dimensional Manifolds
    • L.K. Saul and S.T. Roweis, "Think Globally, Fit Locally: Unsupervised Learning of Low-Dimensional Manifolds," J. Machine Learning Research vol. 4, pp. 119-155, 2003.
    • (2003) J. Machine Learning Research , vol.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2
  • 14
    • 84899010839 scopus 로고    scopus 로고
    • C. Williams and M. Seeger, Using the Nyström Method to Speed Up Kernel Machines, Proc. Advances in Neural Information Processing Systems, pp. 682-6881, 2001.
    • C. Williams and M. Seeger, "Using the Nyström Method to Speed Up Kernel Machines," Proc. Advances in Neural Information Processing Systems, pp. 682-6881, 2001.
  • 17
    • 10844279941 scopus 로고    scopus 로고
    • Efficient Pose Estimation Using View-Based Object Representations
    • G. Peters, "Efficient Pose Estimation Using View-Based Object Representations," Machine Vision and Applications, vol. 16, no. 1, pp. 59-63, 2004.
    • (2004) Machine Vision and Applications , vol.16 , Issue.1 , pp. 59-63
    • Peters, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.