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Volumn 15, Issue 9, 2003, Pages 2227-2254

Bayesian trigonometric support vector classifier

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EID: 0042326376     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976603322297368     Document Type: Article
Times cited : (23)

References (23)
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    • Burges, C.J.C.1
  • 11
    • 0034271876 scopus 로고    scopus 로고
    • The evidence framework applied to support vector machines
    • Kwok, J. T. (2000). The evidence framework applied to support vector machines. IEEE Transactions on Neural Networks, 11(5), 1162-1173.
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    • Kwok, J.T.1
  • 12
    • 0037876458 scopus 로고    scopus 로고
    • Ergodic, primal convergence in dual subgradient schemes for convex programming
    • Larsson, T., Patriksson, M., & Strömberg, A: (1999). Ergodic, primal convergence in dual subgradient schemes for convex programming. Math. Program, 86, 283-312.
    • (1999) Math. Program , vol.86 , pp. 283-312
    • Larsson, T.1    Patriksson, M.2    Strömberg, A.3
  • 13
    • 0002704818 scopus 로고
    • A practical Bayesian framework for back propagation networks
    • MacKay, D. J. C. (1992). A practical Bayesian framework for back propagation networks. Neural Computation, 4(3), 448-472.
    • (1992) Neural Computation , vol.4 , Issue.3 , pp. 448-472
    • MacKay, D.J.C.1
  • 14
    • 0000335983 scopus 로고
    • Bayesian methods for backpropagation networks
    • MacKay, D. J. C. (1994). Bayesian methods for backpropagation networks. Models of Neural Networks, 3, 211-254.
    • (1994) Models of Neural Networks , vol.3 , pp. 211-254
    • MacKay, D.J.C.1
  • 16
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • B. Schölkopf, C. J. C. Burges, & A. J. Smola (Eds.). Cambridge, MA: MIT Press
    • Platt, J. C. (1999). Fast training of support vector machines using sequential minimal optimization. In B. Schölkopf, C. J. C. Burges, & A. J. Smola (Eds.), Advances in kernel methods-Support vector learning (pp. 185-208). Cambridge, MA: MIT Press.
    • (1999) Advances in Kernel Methods-support Vector Learning , pp. 185-208
    • Platt, J.C.1
  • 17
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • A. J. Smola, P. L. Bartlett, B. Schölkopf, & D. Schuurnabs (Eds.). Cambridge, MA: MIT Press
    • Platt, J. C. (2000). Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In A. J. Smola, P. L. Bartlett, B. Schölkopf, & D. Schuurnabs (Eds.), Advances in large margin classifier (pp. 61-73). Cambridge, MA: MIT Press.
    • (2000) Advances in Large Margin Classifier , pp. 61-73
    • Platt, J.C.1
  • 19
    • 0036163572 scopus 로고    scopus 로고
    • Bayesian methods for support vector machines: Evidence and predictive class probabilities
    • Sollich, P. (2002). Bayesian methods for support vector machines: Evidence and predictive class probabilities. Machine Learning, 46, 21-52.
    • (2002) Machine Learning , vol.46 , pp. 21-52
    • Sollich, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.