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Volumn 4, Issue 9, 2008, Pages 2325-2332

Support vector regression with input data uncertainty

Author keywords

Machine learning; Robust estimation; Second order cone program; Support vector regression

Indexed keywords


EID: 63549100038     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (20)

References (15)
  • 2
    • 4043137356 scopus 로고    scopus 로고
    • A tutorial on support vector regression
    • A. Smola and B. Schölkopf, A tutorial on support vector regression, Statistics and Computing, vol. 14, pp. 199-222, 2004.
    • (2004) Statistics and Computing , vol.14 , pp. 199-222
    • Smola, A.1    Schölkopf, B.2
  • 4
    • 33744798398 scopus 로고    scopus 로고
    • Robust convex quadratically constrained programs
    • D. Goldfarb and G. Iyengar, Robust convex quadratically constrained programs, Mathematical Programming, vol. 97, no. 3, pp. 495-515, 2003.
    • (2003) Mathematical Programming , vol.97 , Issue.3 , pp. 495-515
    • Goldfarb, D.1    Iyengar, G.2
  • 5
    • 33745800909 scopus 로고    scopus 로고
    • Second order cone programming approaches for handling missing and uncertain data
    • K. S. Pannagadatta, C. Bhattacharyya and A. Smola, Second order cone programming approaches for handling missing and uncertain data, Journal of Machine Learning Research, vol. 7, pp. 1283-1314, 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1283-1314
    • Pannagadatta, K.S.1    Bhattacharyya, C.2    Smola, A.3
  • 7
    • 0036013023 scopus 로고    scopus 로고
    • Smoothing functions for second-order-cone complementarity problems
    • M. Fukushima, Z. Q. Luo and P. Tseng, Smoothing functions for second-order-cone complementarity problems, SIAM Journal on Optimization, vol. 12, no. 2, pp. 436-460, 2002.
    • (2002) SIAM Journal on Optimization , vol.12 , Issue.2 , pp. 436-460
    • Fukushima, M.1    Luo, Z.Q.2    Tseng, P.3
  • 9
    • 0037844881 scopus 로고    scopus 로고
    • Linear dependency between ε and the input noise in ε-support vector regression
    • J. T. Kwok and I. W. Tsang, Linear dependency between ε and the input noise in ε-support vector regression, IEEE Transactions on Neural Networks, vol. 14, no. 3, pp. 544-553, 2003.
    • (2003) IEEE Transactions on Neural Networks , vol.14 , Issue.3 , pp. 544-553
    • Kwok, J.T.1    Tsang, I.W.2
  • 10
    • 0346250790 scopus 로고    scopus 로고
    • Practical selection of SVM parameters and noise estimation for SVM regression
    • V. Cherkassky and Y. Ma, Practical selection of SVM parameters and noise estimation for SVM regression, Neural Networks, vol. 17, no. 1, pp. 113-126, 2004.
    • (2004) Neural Networks , vol.17 , Issue.1 , pp. 113-126
    • Cherkassky, V.1    Ma, Y.2
  • 12
    • 33846021948 scopus 로고    scopus 로고
    • Second-order cone programming formulations for robust multiclass classification
    • P. Zhong and M. Fukushima, Second-order cone programming formulations for robust multiclass classification, Neural Computation, vol. 19, no. 1, pp. 258-282, 2007.
    • (2007) Neural Computation , vol.19 , Issue.1 , pp. 258-282
    • Zhong, P.1    Fukushima, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.