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Volumn 2388, Issue , 2002, Pages 354-369

Optimization of the SVM kernels using an empirical error minimization scheme

Author keywords

[No Author keywords available]

Indexed keywords

ERRORS; IMAGE RETRIEVAL; OPTIMIZATION; PATTERN RECOGNITION; VECTORS;

EID: 84958774009     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45665-1_28     Document Type: Conference Paper
Times cited : (23)

References (21)
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  • 2
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    • Kmod-a new support vector machine kernel for pattern recognition. Application to digit image recognition
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    • Ayat, N.E.1    Cheriet, M.2    Suen, C.Y.3
  • 4
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    • Bengio, Y.1
  • 6
    • 34249753618 scopus 로고
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    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 9
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    • Making large-scale svm learning practical
    • B. Scholkopf, C. Burges, and A. Smola, editors, chapter 11
    • T. Joachims. Making large-scale svm learning practical. In B. Scholkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods-Support Vector Learning, chapter 11. 1999.
    • (1999) Advances in Kernel Methods-Support Vector Learning
    • Joachims, T.1
  • 10
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • [10] J. Platt. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Advances in large margin classifiers, 10(3), October 1999.
    • (1999) Advances in Large Margin Classifiers , vol.10 , Issue.3
    • Platt, J.1
  • 11
    • 0002229304 scopus 로고    scopus 로고
    • Pairwise classification and support vector machines
    • B. Scholkopf, C. Burges, and A. Smola, editors, chapter Chap. 15
    • [11] U. Kreβel. Pairwise classification and support vector machines. In B. Scholkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods-Support Vector Learning, chapter Chap. 15, pages 255–268. 1999.
    • (1999) Advances in Kernel Methods-Support Vector Learning , pp. 255-268
    • Kreβel, U.1
  • 16
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  • 18
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    • Bayesian methods for support vector machines: Evidence and predictive class probabilities
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    • Sollich, P.1
  • 20
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    • An overview of statistical learning theory
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    • Vapnik, V.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.