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Volumn 14, Issue 3, 2002, Pages 669-688

Orthogonal series density estimation and the kernel eigenvalue problem

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Indexed keywords

ARTICLE;

EID: 0012993529     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976602317250942     Document Type: Article
Times cited : (120)

References (17)
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    • Friedman, J. H., & Tukey, J. W. (1974). A projection pursuit algorithm for exploratory data analysis. IEEE Transactions on Computing, 23, 881-890.
    • (1974) IEEE Transactions on Computing , vol.23 , pp. 881-890
    • Friedman, J.H.1    Tukey, J.W.2
  • 6
    • 0000319005 scopus 로고
    • The estimation of probability densities and cumulatives by Fourier series methods
    • Kronmal, R., & Tarter, M. (1968). The estimation of probability densities and cumulatives by Fourier series methods. Journal of the American Statistical Association, 63, 925-952.
    • (1968) Journal of the American Statistical Association , vol.63 , pp. 925-952
    • Kronmal, R.1    Tarter, M.2
  • 8
    • 0022776702 scopus 로고
    • Can we solve the continuous Karhunen-Loève eigenproblem from discrete data?
    • Ogawa, H., & Oja, E. (1986). Can we solve the continuous Karhunen-Loève eigenproblem from discrete data? Transactions of the IECE of Japan, 69(9), 1020-1029.
    • (1986) Transactions of the IECE of Japan , vol.69 , Issue.9 , pp. 1020-1029
    • Ogawa, H.1    Oja, E.2
  • 10
    • 0006019710 scopus 로고    scopus 로고
    • An expectation maximisation approach to nonlinear component analysis
    • Rosipal, R., & Girolami, M. (2001). An expectation maximisation approach to nonlinear component analysis. Neural Computation, 13(3), 500-505.
    • (2001) Neural Computation , vol.13 , Issue.3 , pp. 500-505
    • Rosipal, R.1    Girolami, M.2
  • 13
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf, B., Smola, A., & Müller, K. R. (1998). Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10(5), 1299-1319.
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.R.3
  • 16
    • 84899010839 scopus 로고    scopus 로고
    • Using the Nyström method to speed up kernel machines
    • T. K. Leen, T. G. Dietterich, & V. Tresp (Eds.), Cambridge, MA: MIT Press
    • Williams, C. K. I., & Seeger, M. (2001). Using the Nyström method to speed up kernel machines. In T. K. Leen, T. G. Dietterich, & V. Tresp (Eds.), Advances in neural information processing systems, 13 (pp. 682-688). Cambridge, MA: MIT Press.
    • (2001) Advances in Neural Information Processing Systems , vol.13 , pp. 682-688
    • Williams, C.K.I.1    Seeger, M.2
  • 17
    • 0039813137 scopus 로고    scopus 로고
    • Gaussian regression and optimal finite dimensional linear models
    • C. M. Bishop (Ed.), Berlin: Springer-Verlag
    • Zhu, H., Williams, C. K. I., Rohwer, R. J., & Morciniec, M. (1998). Gaussian regression and optimal finite dimensional linear models. In C. M. Bishop (Ed.), Neural networks and machine learning. Berlin: Springer-Verlag.
    • (1998) Neural Networks and Machine Learning
    • Zhu, H.1    Williams, C.K.I.2    Rohwer, R.J.3    Morciniec, M.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.