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Volumn 3, Issue , 2003, Pages 2054-2059

Comparison of L1 and L2 Support Vector Machines

Author keywords

[No Author keywords available]

Indexed keywords

LAGRANGE MULTIPLIERS; POLYNOMIALS; PROBLEM SOLVING; VECTORS;

EID: 0141794588     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (17)

References (18)
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    • Pontil, M.1    Verri, A.2
  • 4
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    • Proc. 10th International Conference on Algorithmic Learning Theory, (ALT'99)
    • R. Rifkin, M. Pontil, and A. Verri, "A Note on Support Vector Machine Degeneracy," Proc. 10th International Conference on Algorithmic Learning Theory, (ALT'99). (Lecture Notes in Artificial Intelligence Vol.1720), pp. 252-263, 1999.
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    • Rifkin, R.1    Pontil, M.2    Verri, A.3
  • 5
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    • Behavior of the Weights of a Support Vector Machine as a Function of the Regularization Parameter C
    • R. Fernández, "Behavior of the Weights of a Support Vector Machine as a Function of the Regularization Parameter C," Proc. 8th International Conference on Artificial Neural Networks (ICANN'98), Vol. 2, pp. 917-922, 1998.
    • (1998) Proc. 8th International Conference on Artificial Neural Networks (ICANN'98) , vol.2 , pp. 917-922
    • Fernández, R.1
  • 6
    • 84899002142 scopus 로고    scopus 로고
    • Uniqueness of the SVM Solution
    • S. A. Solla, T. K. Leen, and K.-R. Müller, editors, MIT Press
    • C. J. C. Burges and D. J. Crisp, "Uniqueness of the SVM Solution," In S. A. Solla, T. K. Leen, and K.-R. Müller, editors, Advances in Neural Information Processing Systems 12, pp. 223-229, MIT Press, 2000.
    • (2000) Advances in Neural Information Processing Systems , vol.12 , pp. 223-229
    • Burges, C.J.C.1    Crisp, D.J.2
  • 8
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    • Fuzzy Support Vector Machines for Pattern Classification
    • T. Inoue and S. Abe, "Fuzzy Support Vector Machines for Pattern Classification," Proc. IJCNN'01, pp. 1449-1454, 2001.
    • (2001) Proc. IJCNN'01 , pp. 1449-1454
    • Inoue, T.1    Abe, S.2
  • 11
    • 0000545946 scopus 로고    scopus 로고
    • Convergence of a Generalized SMO Algorithm for SVM Classifier Design
    • S. S. Keerthi and E. G. Gilbert, "Convergence of a Generalized SMO Algorithm for SVM Classifier Design," Machine Learning, Vol. 13, pp. 637-649, 2001.
    • (2001) Machine Learning , vol.13 , pp. 637-649
    • Keerthi, S.S.1    Gilbert, E.G.2
  • 12
    • 0000764772 scopus 로고
    • The Use of Multiple Measurements in Taxonomic Problems
    • R. A. Fisher, "The Use of Multiple Measurements in Taxonomic Problems," Annals of Eugenics, Vol. 7, pp. 179-188, 1936.
    • (1936) Annals of Eugenics , vol.7 , pp. 179-188
    • Fisher, R.A.1
  • 13
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    • Will the Real Iris Data Please Stand up?
    • J. C. Bezdek et al., "Will the Real Iris Data Please Stand up? " IEEE Transactions on Fuzzy Systems, Vol. 7, No. 3, pp. 368-369, 1999.
    • (1999) IEEE Transactions on Fuzzy Systems , vol.7 , Issue.3 , pp. 368-369
    • Bezdek, J.C.1
  • 14
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    • Input Layer Optimization of Neural Networks by Sensitivity Analysis and Its Application to Recognition of Numerals
    • H. Takenaga et al., "Input Layer Optimization of Neural Networks by Sensitivity Analysis and Its Application to Recognition of Numerals," Electrical Engineering in Japan, Vol. 111, No. 4, pp. 130-138, 1991.
    • (1991) Electrical Engineering in Japan , vol.111 , Issue.4 , pp. 130-138
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  • 15
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    • An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
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    • Weiss, S.M.1    Kapouleas, I.2
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.