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Volumn 227, Issue , 2007, Pages 657-664

Dimensionality reduction and generalization

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ERROR ANALYSIS; LEAST SQUARES APPROXIMATIONS; PRINCIPAL COMPONENT ANALYSIS; PROBABILISTIC LOGICS; SUPERVISED LEARNING;

EID: 34547994712     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1273496.1273579     Document Type: Conference Paper
Times cited : (17)

References (17)
  • 1
    • 5844297152 scopus 로고
    • Theory of reproducing kernels
    • Aronszajn, N. (1950). Theory of reproducing kernels. Trans. Amer. Math. Soc., 68, 337-404.
    • (1950) Trans. Amer. Math. Soc , vol.68 , pp. 337-404
    • Aronszajn, N.1
  • 2
    • 1542367492 scopus 로고    scopus 로고
    • Convexity, classification, and risk bounds
    • 638, Department of Statistics, U.C. Berkeley
    • Bartlett, P., Jordan, M., & McAuliffe, J. (2003). Convexity, classification, and risk bounds (Technical Report 638). Department of Statistics, U.C. Berkeley.
    • (2003) Technical Report
    • Bartlett, P.1    Jordan, M.2    McAuliffe, J.3
  • 3
  • 4
    • 3142725535 scopus 로고    scopus 로고
    • Semi-supervised learning on riemannian manifolds
    • Belkin, M., & Niyogi, P. (2004). Semi-supervised learning on riemannian manifolds. Machine Learning, 56, 209-239.
    • (2004) Machine Learning , vol.56 , pp. 209-239
    • Belkin, M.1    Niyogi, P.2
  • 5
    • 84898928351 scopus 로고    scopus 로고
    • Kernel projection machine: A new tool for pattern recognition
    • Blanchard, G., Massart, P., Vert, R., & Zwald, L. (2004). Kernel projection machine: a new tool for pattern recognition. NIPS 2004 (pp. 1649-1656).
    • (2004) NIPS 2004 , pp. 1649-1656
    • Blanchard, G.1    Massart, P.2    Vert, R.3    Zwald, L.4
  • 11
    • 0033459856 scopus 로고    scopus 로고
    • Risk bounds for model selection via penalization
    • Massart, P., Barron, A., & Birge, L. (1999). Risk bounds for model selection via penalization. Proba. Theory Relat.Fields, 113, 301-413.
    • (1999) Proba. Theory Relat.Fields , vol.113 , pp. 301-413
    • Massart, P.1    Barron, A.2    Birge, L.3
  • 13
    • 19544375922 scopus 로고    scopus 로고
    • Kernel principal component regression with em approach to nonlinear principal components extraction
    • CIS, University of Paisley
    • Rosipal, R., Trejo, L., & Cichocki, A. (2000). Kernel principal component regression with em approach to nonlinear principal components extraction (Technical Report). CIS, University of Paisley.
    • (2000) Technical Report
    • Rosipal, R.1    Trejo, L.2    Cichocki, A.3
  • 16
    • 22944490838 scopus 로고    scopus 로고
    • Learning bounds for kernel regression using effective data dimensionality
    • Zhang, T. (2005). Learning bounds for kernel regression using effective data dimensionality. Neural Computation, 17, 2077-2098.
    • (2005) Neural Computation , vol.17 , pp. 2077-2098
    • Zhang, T.1
  • 17
    • 33847676413 scopus 로고    scopus 로고
    • Statistical properties of kernel principal component analyis
    • Zwald, L., Bousquet, O., & Blanchard, G. (2007). Statistical properties of kernel principal component analyis. Machine Learning, 66, 259-294.
    • (2007) Machine Learning , vol.66 , pp. 259-294
    • Zwald, L.1    Bousquet, O.2    Blanchard, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.