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Volumn 15, Issue 2, 2003, Pages 487-507

SMO algorithm for least-squares SVM formulations

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; REGRESSION ANALYSIS;

EID: 0037313407     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976603762553013     Document Type: Article
Times cited : (115)

References (19)
  • 8
    • 84898965347 scopus 로고    scopus 로고
    • A mathematical programming approach to the kernel Fisher algorithm
    • T. K. Leen, T. G. Dietterich, & V. Tresp (Eds.). Cambridge, MA: MIT Press
    • Mika, S., Ratsch, G., & Müller, K. R. (2001). A mathematical programming approach to the kernel Fisher algorithm. In T. K. Leen, T. G. Dietterich, & V. Tresp (Eds.), Advances in neural information processing systems, 13 (pp. 591-597). Cambridge, MA: MIT Press.
    • (2001) Advances in Neural Information Processing Systems , vol.13 , pp. 591-597
    • Mika, S.1    Ratsch, G.2    Müller, K.R.3
  • 9
    • 0033337021 scopus 로고    scopus 로고
    • Fisher discriminant analysis with kernels
    • Y. H. Hu, J. Larsen, E. Wilson, & S. Douglas (Eds.). New York: IEEE
    • Mika, S., Ratsch, G., Weston, J., Schölkopf, B., & Müller, K. R. (1999). Fisher discriminant analysis with kernels. In Y. H. Hu, J. Larsen, E. Wilson, & S. Douglas (Eds.), Neural networks for signal processing IX (pp. 41-48). New York: IEEE.
    • (1999) Neural Networks for Signal Processing IX , pp. 41-48
    • Mika, S.1    Ratsch, G.2    Weston, J.3    Schölkopf, B.4    Müller, K.R.5
  • 11
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • A. Smola, B. Schölkopf, & D. Schuurmans (Eds.), Cambridge, MA: MIT Press
    • Platt, J. (1999). Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In A. Smola, B. Schölkopf, & D. Schuurmans (Eds.), Advances in large margin classifiers. Cambridge, MA: MIT Press.
    • (1999) Advances in Large Margin Classifiers
    • Platt, J.1
  • 12
    • 4243678636 scopus 로고    scopus 로고
    • [Benchmark repository.]
    • Rätsch, G. (1999). [Benchmark repository.] Available on-line at: http://ida.first.gmd.de/̃raetsch/data/benchmarks.htm.
    • (1999)
    • Rätsch, G.1
  • 14
    • 0003401675 scopus 로고    scopus 로고
    • (Neuro-Colt2 Tech. Rep. NC2-TR-1998-030). Berlin: ESPRIT Working Group in Neural and Computational Learning II
    • Smola, A., & Schölkopf, B. (1998) A tutorial on support vector regression (Neuro-Colt2 Tech. Rep. NC2-TR-1998-030). Berlin: ESPRIT Working Group in Neural and Computational Learning II.
    • (1998) A Tutorial on Support Vector Regression
    • Smola, A.1    Schölkopf, B.2
  • 16
    • 0032638628 scopus 로고    scopus 로고
    • Least squares support vector machine classifiers
    • Suykens, J., & Vandewalle, J. (1999). Least squares support vector machine classifiers. Neural Processing Letters, 9, 293-300.
    • (1999) Neural Processing Letters , vol.9 , pp. 293-300
    • Suykens, J.1    Vandewalle, J.2
  • 17
    • 0003551703 scopus 로고
    • (Tech. Rep. SOR-94-15). Princeton, NJ: Statistics and Operations Research, Princeton University
    • Vanderbei, R. J. (1994). LOQO: An interior point code for quadratic programming (Tech. Rep. SOR-94-15). Princeton, NJ: Statistics and Operations Research, Princeton University.
    • (1994) LOQO: An Interior Point Code for Quadratic Programming
    • Vanderbei, R.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.