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Volumn 2, Issue , 2012, Pages 953-961

Accuracy at the top

Author keywords

[No Author keywords available]

Indexed keywords

BETTER PERFORMANCE; CLASSIFICATION ACCURACY; CONVEX OPTIMIZATION PROBLEMS; SCORING FUNCTIONS;

EID: 84877780590     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (84)

References (22)
  • 1
    • 84880083510 scopus 로고    scopus 로고
    • The infinite push: A new support vector ranking algorithm that directly optimizes accuracy at the absolute top of the list
    • S. Agarwal. The infinite push: A new support vector ranking algorithm that directly optimizes accuracy at the absolute top of the list. In Proceedings of the SIAM International Conference on Data Mining, 2011.
    • (2011) Proceedings of the SIAM International Conference on Data Mining
    • Agarwal, S.1
  • 3
    • 0038453192 scopus 로고    scopus 로고
    • Rademacher and Gaussian complexities: Risk bounds and structural results
    • P. L. Bartlett and S. Mendelson. Rademacher and Gaussian complexities: Risk bounds and structural results. Journal of Machine Learning Research, 3:2002, 2002.
    • (2002) Journal of Machine Learning Research , vol.3 , pp. 2002
    • Bartlett, P.L.1    Mendelson, S.2
  • 4
    • 80051762104 scopus 로고    scopus 로고
    • Distributed optimization and statistical learning via the alternating direction method of multipliers
    • S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning, 3(1):1-122, 2011.
    • (2011) Foundations and Trends in Machine Learning , vol.3 , Issue.1 , pp. 1-122
    • Boyd, S.1    Parikh, N.2    Chu, E.3    Peleato, B.4    Eckstein, J.5
  • 8
    • 84864039510 scopus 로고    scopus 로고
    • Learning to rank with nonsmooth cost functions
    • C. J. C. Burges, R. Ragno, and Q. V. Le. Learning to rank with nonsmooth cost functions. In NIPS, pages 193-200, 2006.
    • (2006) NIPS , pp. 193-200
    • Burges, C.J.C.1    Ragno, R.2    Le, Q.V.3
  • 10
    • 55349114379 scopus 로고    scopus 로고
    • Statistical analysis of Bayes optimal subset ranking
    • D. Cossock and T. Zhang. Statistical analysis of Bayes optimal subset ranking. IEEE Transactions on Information Theory, 54(11):5140-5154, 2008.
    • (2008) IEEE Transactions on Information Theory , vol.54 , Issue.11 , pp. 5140-5154
    • Cossock, D.1    Zhang, T.2
  • 15
    • 31844446804 scopus 로고    scopus 로고
    • A support vector method for multivariate performance measures
    • T. Joachims. A support vector method for multivariate performance measures. In ICML, pages 377-384, 2005.
    • (2005) ICML , pp. 377-384
    • Joachims, T.1
  • 16
    • 0001152423 scopus 로고
    • On Bahadur's representation of sample quantiles
    • J. Kiefer. On Bahadur's representation of sample quantiles. Annals of Mathematical Statistics, 38, 1967.
    • (1967) Annals of Mathematical Statistics , vol.38
    • Kiefer, J.1
  • 18
    • 0036104545 scopus 로고    scopus 로고
    • Empirical margin distributions and bounding the generalization error of combined classifiers
    • V. Koltchinskii and D. Panchenko. Empirical margin distributions and bounding the generalization error of combined classifiers. Annals of Statistics, 30, 2002.
    • (2002) Annals of Statistics , vol.30
    • Koltchinskii, V.1    Panchenko, D.2
  • 21
    • 26944478552 scopus 로고    scopus 로고
    • Margin-based ranking meets boosting in the middle
    • C. Rudin, C. Cortes, M. Mohri, and R. E. Schapire. Margin-based ranking meets boosting in the middle. In COLT, pages 63-78, 2005.
    • (2005) COLT , pp. 63-78
    • Rudin, C.1    Cortes, C.2    Mohri, M.3    Schapire, R.E.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.