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Volumn , Issue , 2009, Pages 1153-1160

Online learning by ellipsoid method

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; EFFICIENT ALGORITHM; ELLIPSOID METHOD; MISTAKE BOUNDS; ONLINE LEARNING; ONLINE LEARNING ALGORITHMS; POSITIVE-DEFINITE MATRICES; TRAINING EXAMPLE; TWO-STATE;

EID: 71149118387     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (17)
  • 4
    • 0010442827 scopus 로고    scopus 로고
    • On the algorithmic implementation of multiclass kernel-based vector machines
    • Crammer, K., & Singer, Y (2002). On the algorithmic implementation of multiclass kernel-based vector machines. J. Mach. Learn. Res., 2, 265-292.
    • (2002) J. Mach. Learn. Res , vol.2 , pp. 265-292
    • Crammer, K.1    Singer, Y.2
  • 5
    • 0141496132 scopus 로고    scopus 로고
    • Ultraconservative online algorithms for multiclass problems
    • Crammer, K., & Singer, Y. (2003). Ultraconservative online algorithms for multiclass problems. J. Mach. Learn. Res., 3, 951-991.
    • (2003) J. Mach. Learn. Res , vol.3 , pp. 951-991
    • Crammer, K.1    Singer, Y.2
  • 7
    • 84868111801 scopus 로고    scopus 로고
    • A new approximate maximal margin classification algorithm
    • Gentile, C. (2002). A new approximate maximal margin classification algorithm. J. Mach. Learn. Res., 2, 213-242.
    • (2002) J. Mach. Learn. Res , vol.2 , pp. 213-242
    • Gentile, C.1
  • 9
    • 0035370643 scopus 로고    scopus 로고
    • General convergence results for linear discriminant updates
    • Grove, A. J., Littlestone, N., & Schuurmans, D. (2001). General convergence results for linear discriminant updates. Mach. Learn., 43, 173-210.
    • (2001) Mach. Learn , vol.43 , pp. 173-210
    • Grove, A.J.1    Littlestone, N.2    Schuurmans, D.3
  • 11
    • 0008815681 scopus 로고    scopus 로고
    • Additive versus exponentiated gradient updates for linear prediction
    • Kivinen, J., & M.K. Warmuth (1997). Additive versus exponentiated gradient updates for linear prediction. Information and Computation, 132, 1-64.
    • (1997) Information and Computation , vol.132 , pp. 1-64
    • Kivinen, J.1    Warmuth, M.K.2
  • 12
    • 3543110224 scopus 로고    scopus 로고
    • Kivinen, J., Smola, A. J., & C. Williamson, R. (2002). Online learning with kernels. IEEE Transactions on Signal Processing, 52, 2165-2176.
    • Kivinen, J., Smola, A. J., & C. Williamson, R. (2002). Online learning with kernels. IEEE Transactions on Signal Processing, 52, 2165-2176.
  • 13
    • 0036161258 scopus 로고    scopus 로고
    • The relaxed online maximum margin algorithm
    • Li, Y., & Long, P. M. (2002). The relaxed online maximum margin algorithm. Mach. Learn., 46, 361-387.
    • (2002) Mach. Learn , vol.46 , pp. 361-387
    • Li, Y.1    Long, P.M.2
  • 15
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65, 386-407.
    • (1958) Psychological Review , vol.65 , pp. 386-407
    • Rosenblatt, F.1
  • 17
    • 0002252730 scopus 로고
    • Cut-off method with space extension in convex programming problems
    • Shor, N. (1977). Cut-off method with space extension in convex programming problems. Cybernetics, 12, 94-94.
    • (1977) Cybernetics , vol.12 , pp. 94-94
    • Shor, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.