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Volumn , Issue , 2004, Pages 639-646

Learning with non-positive kernels

Author keywords

Ill posed Problems; Indefinite Kernels; Non convex Optimization; Rademacher Average; Representer Theorem; Reproducing Kernel Kre n Space

Indexed keywords

APPROXIMATION THEORY; COSTS; EIGENVALUES AND EIGENFUNCTIONS; ITERATIVE METHODS; MATRIX ALGEBRA; PROBLEM SOLVING; SET THEORY; SPURIOUS SIGNAL NOISE;

EID: 14344254996     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (173)

References (18)
  • 7
    • 0001273835 scopus 로고
    • Regularisation methods for large-scale problems
    • Hanke, M., & Hansen, P. (1993). Regularisation methods for large-scale problems. Surveys Math. Ind., 3, 253-315.
    • (1993) Surveys Math. Ind. , vol.3 , pp. 253-315
    • Hanke, M.1    Hansen, P.2
  • 11
    • 35248851077 scopus 로고    scopus 로고
    • A few notes on statistical learning theory
    • Springer Verlag
    • Mendelson, S. (2003). A few notes on statistical learning theory. Advanced Lectures in Machine Learning (pp. 1-40). Springer Verlag.
    • (2003) Advanced Lectures in Machine Learning , pp. 1-40
    • Mendelson, S.1
  • 13
    • 0004267646 scopus 로고    scopus 로고
    • Princeton Univ. Pr. Reprint edition
    • Rockafellar, R. T. (1996). Convex analysis. Princeton Univ. Pr. Reprint edition.
    • (1996) Convex Analysis
    • Rockafellar, R.T.1
  • 16
    • 0037579303 scopus 로고    scopus 로고
    • Regularization with dot-product kernels
    • Smola, A. J., Ovari, Z. L., & Williamson, R. C. (2000). Regularization with dot-product kernels. NIPS (pp. 308-314).
    • (2000) NIPS , pp. 308-314
    • Smola, A.J.1    Ovari, Z.L.2    Williamson, R.C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.