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Volumn 4668 LNCS, Issue PART 1, 2007, Pages 139-148

Resilient approximation of kernel classifiers

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; CLASSIFICATION (OF INFORMATION); GRADIENT METHODS; SUPPORT VECTOR MACHINES;

EID: 38149089662     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74690-4_15     Document Type: Conference Paper
Times cited : (4)

References (16)
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    • Mozer, M, Jordan, M, Petsche, T, eds, Advances in Neural Information Processing Systems, Cambridge, MA
    • Burges, C.J.C., Schölkopf, B.: Improving the accuracy and speed of support vector machines. In: Mozer, M., Jordan, M., Petsche, T. (eds.) Advances in Neural Information Processing Systems, Cambridge, MA, vol. 9, pp. 375-381 (1997)
    • (1997) Improving the accuracy and speed of support vector machines , vol.9 , pp. 375-381
    • Burges, C.J.C.1    Schölkopf, B.2
  • 4
    • 0000263906 scopus 로고    scopus 로고
    • Fast approximation of support vector kernel expansions, and an interpretation of clustering as approximation in feature space
    • Levi, P, Ahlers, R.J, May, F, Schanz, M, eds, Springer, Heidelberg
    • Schölkopf, B., Knirsch, P., Smola, A.J., Burges, C.J.C.: Fast approximation of support vector kernel expansions, and an interpretation of clustering as approximation in feature space. In: Levi, P., Ahlers, R.J., May, F., Schanz, M. (eds.) DAGM-Symposium, pp. 124-132. Springer, Heidelberg (1998)
    • (1998) DAGM-Symposium , pp. 124-132
    • Schölkopf, B.1    Knirsch, P.2    Smola, A.J.3    Burges, C.J.C.4
  • 7
    • 0037238922 scopus 로고    scopus 로고
    • Empirical evaluation of the improved Rprop learning algorithm
    • Igel, C., Hüsken, M.: Empirical evaluation of the improved Rprop learning algorithm. Neurocomputing 50(C), 105-123 (2003)
    • (2003) Neurocomputing , vol.50 , Issue.C , pp. 105-123
    • Igel, C.1    Hüsken, M.2
  • 8
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C., Vapnik, V.: Support-vector networks. Machine Learning 20(3), 273-297 (1995)
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 9
    • 33745784639 scopus 로고    scopus 로고
    • Maximum-gain working set selection for support vector machines
    • Glasmachers, T., Igel, C.: Maximum-gain working set selection for support vector machines. Journal of Machine Learning Research 7, 1437-1466 (2006)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1437-1466
    • Glasmachers, T.1    Igel, C.2
  • 11
    • 0036565280 scopus 로고    scopus 로고
    • Mercer kernel-based clustering in feature space
    • Girolami, M.: Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks 13(3), 780-784 (2002)
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.3 , pp. 780-784
    • Girolami, M.1
  • 13
    • 0028466750 scopus 로고
    • Advanced supervised learning in multi-layer perceptrons - From backpropagation to adaptive learning algorithms
    • Riedmiller, M.: Advanced supervised learning in multi-layer perceptrons - From backpropagation to adaptive learning algorithms. Computer Standards and Interfaces 16(5), 265-278 (1994)
    • (1994) Computer Standards and Interfaces , vol.16 , Issue.5 , pp. 265-278
    • Riedmiller, M.1
  • 16
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proceedings of the IEEE 86(11), 2278-2324 (1998)
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.