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Volumn 3559 LNAI, Issue , 2005, Pages 48-62

Loss bounds for online category ranking

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; PROBLEM SOLVING;

EID: 26944437032     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11503415_4     Document Type: Conference Paper
Times cited : (5)

References (12)
  • 1
    • 0035370926 scopus 로고    scopus 로고
    • Relative loss bounds for on-line density estimation with the exponential family of distributions
    • K.S. Azoury and M.W. Warmuth. Relative loss bounds for on-line density estimation with the exponential family of distributions. Machine Learning, 43(3):211-246, 2001.
    • (2001) Machine Learning , vol.43 , Issue.3 , pp. 211-246
    • Azoury, K.S.1    Warmuth, M.W.2
  • 2
    • 49949144765 scopus 로고
    • The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
    • L. M. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming. USSR Computational Mathematics and Mathematical Physics, 7:200-217, 1967.
    • (1967) USSR Computational Mathematics and Mathematical Physics , vol.7 , pp. 200-217
    • Bregman, L.M.1
  • 4
    • 0036643072 scopus 로고    scopus 로고
    • Logistic regression, AdaBoost and Bregman distances
    • M. Collins, R.E. Schapire, and Y Singer. Logistic regression, AdaBoost and Bregman distances. Machine Learning, 47(2/3):253-285, 2002.
    • (2002) Machine Learning , vol.47 , Issue.2-3 , pp. 253-285
    • Collins, M.1    Schapire, R.E.2    Singer, Y.3
  • 8
    • 0142228873 scopus 로고    scopus 로고
    • A new family of online algorithms for category ranking
    • K. Crammer and Y. Singer. A new family of online algorithms for category ranking. Jornal of Machine Learning Research, 3:1025-1058, 2003.
    • (2003) Jornal of Machine Learning Research , vol.3 , pp. 1025-1058
    • Crammer, K.1    Singer, Y.2
  • 9
    • 0141496132 scopus 로고    scopus 로고
    • Ultraconservative online algorithms for multiclass problems
    • K. Crammer and Y. Singer. Ultraconservative online algorithms for multiclass problems. Jornal of Machine Learning Research, 3:951-991, 2003.
    • (2003) Jornal of Machine Learning Research , vol.3 , pp. 951-991
    • Crammer, K.1    Singer, Y.2
  • 12
    • 0033281701 scopus 로고    scopus 로고
    • Improved boosting algorithms using confidence-rated predictions
    • R. E. Schapire and Y. Singer. Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37(3):1-40, 1999.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 1-40
    • Schapire, R.E.1    Singer, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.