메뉴 건너뛰기




Volumn 71, Issue 7-9, 2008, Pages 1230-1237

Kernel-based online machine learning and support vector reduction

Author keywords

Budget algorithm; Classifier complexity reduction; Online SVMs; Span of support vectors; Support vector machines

Indexed keywords

CLASSIFICATION (OF INFORMATION); E-LEARNING; LEARNING ALGORITHMS; ONLINE SYSTEMS;

EID: 40649103591     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.11.023     Document Type: Article
Times cited : (60)

References (20)
  • 4
    • 0141496132 scopus 로고    scopus 로고
    • Ultraconservative online algorithms for multiclass problems
    • Crammer K., and Singer Y. Ultraconservative online algorithms for multiclass problems. J. Mach. Learn. Res. 3 (2003) 951-991
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 951-991
    • Crammer, K.1    Singer, Y.2
  • 6
    • 0001260194 scopus 로고    scopus 로고
    • Exact simplification of support vector solutions
    • Downs T., Gates K.E., and Masters A. Exact simplification of support vector solutions. J. Mach. Learn. Res. 2 (2001) 293-297
    • (2001) J. Mach. Learn. Res. , vol.2 , pp. 293-297
    • Downs, T.1    Gates, K.E.2    Masters, A.3
  • 7
    • 0041494125 scopus 로고    scopus 로고
    • Efficient svm training using low-rank kernel representations
    • Fine S., and Scheinberg K. Efficient svm training using low-rank kernel representations. J. Mach. Learn. Res. 2 (2001) 243-264
    • (2001) J. Mach. Learn. Res. , vol.2 , pp. 243-264
    • Fine, S.1    Scheinberg, K.2
  • 8
    • 0036158552 scopus 로고    scopus 로고
    • A simple decomposition method for support vector machines
    • Hsu C.-W., and Lin C.-J. A simple decomposition method for support vector machines. Mach. Learn. 46 (2002) 291-314
    • (2002) Mach. Learn. , vol.46 , pp. 291-314
    • Hsu, C.-W.1    Lin, C.-J.2
  • 9
    • 33745789043 scopus 로고    scopus 로고
    • Building support vector machines with reduced classifier complexity
    • Keerthi S.S., Chapelle O., and DeCoste D. Building support vector machines with reduced classifier complexity. J. Mach. Learn. Res. 7 (2006) 1493-1515
    • (2006) J. Mach. Learn. Res. , vol.7 , pp. 1493-1515
    • Keerthi, S.S.1    Chapelle, O.2    DeCoste, D.3
  • 10
    • 0033640690 scopus 로고    scopus 로고
    • A fast iterative nearest point algorithm for support vector machine classifier design
    • Keerthi S.S., Shevade S.K., Bhattacharyya C., and Murthy K.R.K. A fast iterative nearest point algorithm for support vector machine classifier design. IEEE Trans. Neural Networks 11 1 (2000) 124-136
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.1 , pp. 124-136
    • Keerthi, S.S.1    Shevade, S.K.2    Bhattacharyya, C.3    Murthy, K.R.K.4
  • 13
    • 31844434496 scopus 로고    scopus 로고
    • An efficient method for simplifying support vector machines
    • Bonn, Germany
    • Nguyen D., and Ho T. An efficient method for simplifying support vector machines. 22nd International Conference on Machine Learning. Bonn, Germany (2005) 617-624
    • (2005) 22nd International Conference on Machine Learning , pp. 617-624
    • Nguyen, D.1    Ho, T.2
  • 16
    • 4644354708 scopus 로고    scopus 로고
    • Sparseness of support vector machines
    • Steinwart I. Sparseness of support vector machines. J. Mach. Learn. Res. 4 (2003) 1071-1105
    • (2003) J. Mach. Learn. Res. , vol.4 , pp. 1071-1105
    • Steinwart, I.1
  • 17
    • 0001224048 scopus 로고    scopus 로고
    • Sparse Bayesian learning and the relevance vector machine
    • Tipping M.E. Sparse Bayesian learning and the relevance vector machine. J. Mach. Learn. Res. 1 (2001) 211-214
    • (2001) J. Mach. Learn. Res. , vol.1 , pp. 211-214
    • Tipping, M.E.1
  • 19
    • 0034264380 scopus 로고    scopus 로고
    • Bounds on error expectation for support vector machines
    • Vapnik V., and Chapelle O. Bounds on error expectation for support vector machines. Neural Comput. 12 9 (2000) 2013-2036
    • (2000) Neural Comput. , vol.12 , Issue.9 , pp. 2013-2036
    • Vapnik, V.1    Chapelle, O.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.