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Volumn 70, Issue 13-15, 2007, Pages 2528-2533

Incremental support vector machines and their geometrical analyses

Author keywords

Admissible region; Incremental learning; Learning curves; Support vector machines

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL GEOMETRY; ITERATIVE METHODS; QUADRATIC PROGRAMMING; SET THEORY;

EID: 34249683794     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2006.07.013     Document Type: Article
Times cited : (15)

References (16)
  • 2
    • 0000788596 scopus 로고
    • The convex hull of a random set of points
    • Efron B. The convex hull of a random set of points. Biometrika 52 (1965) 331-343
    • (1965) Biometrika , vol.52 , pp. 331-343
    • Efron, B.1
  • 4
    • 3042665660 scopus 로고    scopus 로고
    • An asymptotic statistical theory of polynomial kernel methods
    • Ikeda K. An asymptotic statistical theory of polynomial kernel methods. Neural Comput. 16 8 (2004) 1705-1719
    • (2004) Neural Comput. , vol.16 , Issue.8 , pp. 1705-1719
    • Ikeda, K.1
  • 5
    • 0842310256 scopus 로고    scopus 로고
    • Boundedness of input space and effective dimension of feature space in kernel methods
    • Ikeda K. Boundedness of input space and effective dimension of feature space in kernel methods. IEICE Trans. Inf. Syst. E87-D (2004) 297-299
    • (2004) IEICE Trans. Inf. Syst. , vol.E87-D , pp. 297-299
    • Ikeda, K.1
  • 6
    • 33144475013 scopus 로고    scopus 로고
    • Effects of kernel function on Nu support vector machines in asymptotics
    • Ikeda K. Effects of kernel function on Nu support vector machines in asymptotics. IEEE Trans. Neural Networks 17 1 (2006) 1-9
    • (2006) IEEE Trans. Neural Networks , vol.17 , Issue.1 , pp. 1-9
    • Ikeda, K.1
  • 7
    • 33645233144 scopus 로고    scopus 로고
    • Geometrical properties of lifting-up in the Nu support vector machines
    • Ikeda K. Geometrical properties of lifting-up in the Nu support vector machines. IEICE Trans. Inf. Syst. E89-D (2006) 847-852
    • (2006) IEICE Trans. Inf. Syst. , vol.E89-D , pp. 847-852
    • Ikeda, K.1
  • 8
    • 33746218431 scopus 로고    scopus 로고
    • Geometry of admissible parameter region in neural learning
    • Ikeda K., and Amari S.-I. Geometry of admissible parameter region in neural learning. IEICE Trans. Fundam. E79-A (1996) 938-943
    • (1996) IEICE Trans. Fundam. , vol.E79-A , pp. 938-943
    • Ikeda, K.1    Amari, S.-I.2
  • 9
    • 19344364266 scopus 로고    scopus 로고
    • An asymptotic statistical analysis of support vector machines with soft margins
    • Ikeda K., and Aoishi T. An asymptotic statistical analysis of support vector machines with soft margins. Neural Networks 18 3 (2005) 251-259
    • (2005) Neural Networks , vol.18 , Issue.3 , pp. 251-259
    • Ikeda, K.1    Aoishi, T.2
  • 10
    • 25144470140 scopus 로고    scopus 로고
    • Geometrical properties of Nu support vector machines with different norms
    • Ikeda K., and Murata N. Geometrical properties of Nu support vector machines with different norms. Neural Comput. 17 11 (2005) 2508-2529
    • (2005) Neural Comput. , vol.17 , Issue.11 , pp. 2508-2529
    • Ikeda, K.1    Murata, N.2
  • 14
    • 0003652453 scopus 로고    scopus 로고
    • Smola A.J., Bartlett P.L., Schölkopf B., and Schuurmans D. (Eds), MIT Press, Cambridge, MA
    • In: Smola A.J., Bartlett P.L., Schölkopf B., and Schuurmans D. (Eds). Advances in Large Margin Classifiers (2000), MIT Press, Cambridge, MA
    • (2000) Advances in Large Margin Classifiers


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.