Up:Kernel
Principal Component AnalysisPrevious:Links
Bibliography
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S. Mika, B. Schölkopf, A. Smola, K.-R. Müller, M. Scholz, and
G. Rätsch.
Kernel PCA and de-noising in feature spaces.
In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances
in Neural Information Processing Systems, volume 11, pages 536-542.
MIT Press, Cambridge, MA, 1999.
Download from HERE.
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P. M. Murphy and D. W. Aha.
UCI Repository of machine learning databases, 1994.
Available from:
www.ics.uci.edu/~mlearn/MLRepository.html.
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B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors.
Advances in Kernel Methods - Support Vector Learning.
MIT Press, Cambridge, MA, 1999.
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B. Schölkopf, S. Mika, A. Smola, G. Rätsch, and K.-R. Müller.
Kernel PCA pattern reconstruction via approximate pre-images.
In L. Niklasson, M. Bodén, and T. Ziemke, editors, Proceedings
of the 8th International Conference on Artificial Neural Networks, Perspectives
in Neural Computing, pages 147-152. Springer Verlag, Berlin, 1998.
Download from HERE.
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B. Schölkopf, A. Smola, and K.-R. Müller.
Nonlinear component analysis as a kernel eigenvalue problem.
Neural Computation, 10:1299-1319, 1998.
Download from HERE.
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B. Schölkopf, A. Smola, and K.-R. Müller.
Kernel principal component analysis.
In B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors, Advances
in Kernel Methods - Support Vector Learning, pages 327-352. MIT
Press, Cambridge, MA, 1999.
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C. J. Twining and C. J. Taylor.
Kernel principal component analysis and the construction of non-linear
active shape models.
In T. Cootes and C. J. Taylor, editors, Proceedings of BMVC20001,
Manchester, UK, volume 1, pages 23-32. BMVA.
Carole Twining
2001-10-02