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Volumn , Issue , 2009, Pages 1150-1155

Spectral kernel learning for semi-supervised classification

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; GRAPH THEORY; LINEAR PROGRAMMING; SUPERVISED LEARNING;

EID: 78149492457     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (18)
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    • Manifold regularization: A geometric framework for learning from examples
    • 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.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 3
    • 33947233031 scopus 로고    scopus 로고
    • Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering
    • Y. Bengio, J. F. Paiement, P. Vincent, O. Delalleau, N. L. Roux, and M. Ouimet. Out-of-sample extensions for lle, isomap, mds, eigenmaps, and spectral clustering. In NIPS 16, 2004.
    • (2004) NIPS , vol.16
    • Bengio, Y.1    Paiement, J.F.2    Vincent, P.3    Delalleau, O.4    Roux, N.L.5    Ouimet, M.6
  • 7
    • 84864031835 scopus 로고    scopus 로고
    • Manifold denoising
    • M. Hein and M. Maier. Manifold denoising. In NIPS 19, 2007.
    • (2007) NIPS , vol.19
    • Hein, M.1    Maier, M.2
  • 8
    • 33749589757 scopus 로고    scopus 로고
    • Learning the unified kernel machines for classification
    • S. Hoi, M. Lyu, and E. Chang. Learning the unified kernel machines for classification. In Proc. KDD, 2006.
    • Proc. KDD, 2006
    • Hoi, S.1    Lyu, M.2    Chang, E.3
  • 9
    • 0041775676 scopus 로고    scopus 로고
    • Diffusion kernels on graphs and other discrete input spaces
    • R. I. Kondor and J. Lafferty. Diffusion kernels on graphs and other discrete input spaces. In Proc. ICML, 2002.
    • Proc. ICML, 2002
    • Kondor, R.I.1    Lafferty, J.2
  • 11
    • 84899013108 scopus 로고    scopus 로고
    • On spectral clustering: Analysis and an algorithm
    • A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS 14, 2002.
    • (2002) NIPS , vol.14
    • Ng, A.Y.1    Jordan, M.I.2    Weiss, Y.3
  • 12
    • 33847702103 scopus 로고    scopus 로고
    • The principal components analysis of a graph, and its relationships to spectral clustering
    • M. Saerens, F. Fouss, L. Yen, and P. Dupont. The principal components analysis of a graph, and its relationships to spectral clustering. In Proc. ECML, 2004.
    • Proc. ECML, 2004
    • Saerens, M.1    Fouss, F.2    Yen, L.3    Dupont, P.4
  • 14
    • 31844440904 scopus 로고    scopus 로고
    • Beyond the point cloud: From transductive to semi-supervised learning
    • V. Sindhwani, P. Niyogi, and M. Belkin. Beyond the point cloud: from transductive to semi-supervised learning. In Proc. ICML, 2005.
    • Proc. ICML, 2005
    • Sindhwani, V.1    Niyogi, P.2    Belkin, M.3
  • 15
    • 33749647871 scopus 로고    scopus 로고
    • Analysis of spectral kernel design based semi-supervised learning
    • T. Zhang and R. Ando. Analysis of spectral kernel design based semi-supervised learning. In NIPS 18, 2006.
    • (2006) NIPS , vol.18
    • Zhang, T.1    Ando, R.2
  • 17
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    • Semi-supervised learning using gaussian fields and harmonic functions
    • X. Zhu, Z. Ghahramani, and J. Lafferty. Semi-supervised learning using gaussian fields and harmonic functions. In Proc. ICML, 2003.
    • Proc. ICML, 2003
    • Zhu, X.1    Ghahramani, Z.2    Lafferty, J.3
  • 18
    • 84899028404 scopus 로고    scopus 로고
    • Nonparametric transforms of graph kernels for semi-supervised learning
    • X. Zhu, J. Kandola, Z. Ghahramani, and J. Lafferty. Nonparametric transforms of graph kernels for semi-supervised learning. In NIPS 17, 2005.
    • (2005) NIPS , vol.17
    • Zhu, X.1    Kandola, J.2    Ghahramani, Z.3    Lafferty, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.