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Volumn , Issue , 2000, Pages 512-518

Boosting algorithms as gradient descent

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE BOOSTING; COST FUNCTIONS;

EID: 84898978212     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (766)

References (19)
  • 1
    • 0032028728 scopus 로고    scopus 로고
    • The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the network
    • March
    • P. L. Bartlett. The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network. IEEE Transactions on Information Theory, 44(2):525-536, March 1998.
    • (1998) IEEE Transactions on Information Theory , vol.44 , Issue.2 , pp. 525-536
    • Bartlett, P.L.1
  • 2
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman. Bagging predictors. Machine Learning, 24(2):123-140, 1996.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 3
    • 0003929807 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • University of California, Berkeley
    • L. Breiman. Prediction games and arcing algorithms. Technical Report 504, Department of Statistics, University of California, Berkeley, 1998.
    • (1998) Technical Report 504, Department of Statistics
    • Breiman, L.1
  • 5
    • 0001823341 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Oregon State University
    • T.G. Dietterich. An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Technical report, Computer Science Department, Oregon State University, 1998.
    • (1998) Technical Report, Computer Science Department
    • Dietterich, T.G.1
  • 10
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • August
    • Y. Preund and R. E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1): 119-139, August 1997.
    • (1997) Journal of Computer and System Sciences , vol.55 , Issue.1 , pp. 119-139
    • Preund, Y.1    Schapire, R.E.2
  • 14
    • 0033870982 scopus 로고    scopus 로고
    • Improved generalization through explicit optimization of margins
    • to appear
    • L. Mason, P. L. Bartlett, and J. Baxter. Improved generalization through explicit optimization of margins. Machine Learning, 1999. (to appear).
    • (1999) Machine Learning
    • Mason, L.1    Bartlett, P.L.2    Baxter, J.3
  • 15
    • 0002550596 scopus 로고    scopus 로고
    • Functional gradient techniques for combining hypotheses
    • Alex Smola, Peter Bartlett, Bernard Schölkopf, and Dale Schurmanns, editors, To appear MIT Press
    • Llew Mason, Jonathan Baxter, Peter Bartlett, and Marcus Frean. Functional Gradient Techniques for Combining Hypotheses. In Alex Smola, Peter Bartlett, Bernard Schölkopf, and Dale Schurmanns, editors, Large Margin Classifiers. MIT Press, 1999. To appear.
    • (1999) Large Margin Classifiers
    • Mason, L.1    Baxter, J.2    Bartlett, P.3    Frean, M.4
  • 17
    • 0003851811 scopus 로고    scopus 로고
    • Soft margins for adaboost
    • Department of Computer Science, Royal Holloway, University of London, Egham, UK
    • G. Rätsch, T. Onoda, and K.-R. Müller. Soft margins for AdaBoost. Technical Report NC-TR-1998-021, Department of Computer Science, Royal Holloway, University of London, Egham, UK, 1998.
    • (1998) Technical Report NC-TR-1998-021
    • Rätsch, G.1    Onoda, T.2    Müller, K.-R.3
  • 18
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin : A new explanation for the effectiveness of voting methods
    • October
    • R. E. Schapire, Y. Preund, P. L. Bartlett, and W. S. Lee. Boosting the margin : A new explanation for the effectiveness of voting methods. Annals of Statistics, 26(5): 1651-1686, October 1998.
    • (1998) Annals of Statistics , vol.26 , Issue.5 , pp. 1651-1686
    • Schapire, R.E.1    Preund, Y.2    Bartlett, P.L.3    Lee, W.S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.