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Volumn 4539 LNAI, Issue , 2007, Pages 142-156

Suboptimality of penalized empirical risk minimization in classification

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); FUNCTION EVALUATION; OPTIMAL SYSTEMS; OPTIMIZATION; PROBLEM SOLVING;

EID: 38049026180     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72927-3_12     Document Type: Conference Paper
Times cited : (15)

References (36)
  • 1
    • 33746043351 scopus 로고    scopus 로고
    • Audibert, J.-Y.: A randomized online learning algorithm for better variance control. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), 4005, pp. 392-407. Springer, Heidelberg (2006)
    • Audibert, J.-Y.: A randomized online learning algorithm for better variance control. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), vol. 4005, pp. 392-407. Springer, Heidelberg (2006)
  • 2
    • 33746060718 scopus 로고    scopus 로고
    • Mixture density estimation
    • Barron, A., Li, J.: Mixture density estimation. Biometrics 53, 603-618 (1997)
    • (1997) Biometrics , vol.53 , pp. 603-618
    • Barron, A.1    Li, J.2
  • 6
    • 0043289776 scopus 로고    scopus 로고
    • Analyzing bagging
    • Bühlmann, P., Yu, B.: Analyzing bagging. Ann. Statist. 30(4), 927-961 (2002)
    • (2002) Ann. Statist , vol.30 , Issue.4 , pp. 927-961
    • Bühlmann, P.1    Yu, B.2
  • 7
    • 0345234052 scopus 로고    scopus 로고
    • Statistical Learning Theory and Stochastic Optimization
    • Ecole d'été de Probabilités de Saint-Flour 2001, Springer, Heidelberg
    • Catoni, O.: Statistical Learning Theory and Stochastic Optimization. Ecole d'été de Probabilités de Saint-Flour 2001. Lecture Notes in Mathematics. Springer, Heidelberg (2001)
    • (2001) Lecture Notes in Mathematics
    • Catoni, O.1
  • 9
    • 38049043618 scopus 로고    scopus 로고
    • Adapting to unknown smoothness by aggregation of thresholded wavelet estimators
    • Submitted
    • Chesneau, C., Lecué, G.: Adapting to unknown smoothness by aggregation of thresholded wavelet estimators. Submitted (2006)
    • (2006)
    • Chesneau, C.1    Lecué, G.2
  • 10
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C., Vapnik, V.: Support-vector networks. Machine Learning 20(3), 273-297 (1995)
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 12
    • 0030371765 scopus 로고    scopus 로고
    • Some Universal Results on the Behavior of Increments of Partial Sums
    • Einmahl, U., Mason, D.: Some Universal Results on the Behavior of Increments of Partial Sums. Ann. Probab. 24, 2626-2635 (1996)
    • (1996) Ann. Probab , vol.24 , pp. 2626-2635
    • Einmahl, U.1    Mason, D.2
  • 13
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoric generalization of on-line learning and an application to boosting
    • Freund, Y., Schapire, R.: A decision-theoric generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55, 119-139 (1997)
    • (1997) Journal of Computer and System Sciences , vol.55 , pp. 119-139
    • Freund, Y.1    Schapire, R.2
  • 14
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting. Ann. Statist. 28, 337-407 (2000)
    • (2000) Ann. Statist , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 15
    • 0032164946 scopus 로고
    • Sequential prediction of individual sequences under general loss functions
    • Haussler, D., Kivinen, J., Warmuth, M.K.: Sequential prediction of individual sequences under general loss functions. IEEE Trans. on Information Theory 44(5), 1906-1925
    • (1906) IEEE Trans. on Information Theory , vol.44 , Issue.5
    • Haussler, D.1    Kivinen, J.2    Warmuth, M.K.3
  • 16
    • 33746619670 scopus 로고    scopus 로고
    • Bayesian regression using akaike priors. Yale University, New Haven
    • Preprint
    • Hartigan, J.: Bayesian regression using akaike priors. Yale University, New Haven, Preprint (2002)
    • (2002)
    • Hartigan, J.1
  • 19
    • 84947774618 scopus 로고    scopus 로고
    • Averaging expert predictions
    • Fischer, P, Simon, H.U, eds, EuroCOLT 1999, Springer, Heidelberg
    • Kivinen, J., Warmuth, M.K.: Averaging expert predictions. In: Fischer, P., Simon, H.U. (eds.) EuroCOLT 1999. LNCS (LNAI), vol. 1572, pp. 153-167. Springer, Heidelberg (1999)
    • (1999) LNCS (LNAI , vol.1572 , pp. 153-167
    • Kivinen, J.1    Warmuth, M.K.2
  • 20
    • 33746194045 scopus 로고    scopus 로고
    • Local Rademacher Complexities and Oracle Inequalities in Risk Minimization (IMS Medallion Lecture)
    • Koltchinskii, V.: Local Rademacher Complexities and Oracle Inequalities in Risk Minimization (IMS Medallion Lecture). Ann. Statist. 34(6), 1-50 (2006)
    • (2006) Ann. Statist , vol.34 , Issue.6 , pp. 1-50
    • Koltchinskii, V.1
  • 21
    • 38049039502 scopus 로고    scopus 로고
    • Optimal rates of aggregation in classification
    • Submitted
    • Lecué, G.: Optimal rates of aggregation in classification. Submitted (2005)
    • (2005)
    • Lecué, G.1
  • 23
    • 33746090509 scopus 로고    scopus 로고
    • Lecué, G.: Optimal oracle inequality for aggregation of classifiers under low noise condition. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), 4005, pp. 364-378. Springer, Heidelberg (2006)
    • Lecué, G.: Optimal oracle inequality for aggregation of classifiers under low noise condition. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), vol. 4005, pp. 364-378. Springer, Heidelberg (2006)
  • 24
    • 38049063223 scopus 로고    scopus 로고
    • Suboptimality of Penalized Empirical Risk Minimization
    • Manuscript
    • Lecué, G.: Suboptimality of Penalized Empirical Risk Minimization. Manuscript (2006)
    • (2006)
    • Lecué, G.1
  • 25
    • 33746478298 scopus 로고    scopus 로고
    • Information theory and mixing least-square regressions
    • Leung, G., Barron, A.: Information theory and mixing least-square regressions. IEEE Transactions on Information Theory 52(8), 3396-3410 (2006)
    • (2006) IEEE Transactions on Information Theory , vol.52 , Issue.8 , pp. 3396-3410
    • Leung, G.1    Barron, A.2
  • 26
    • 9444269961 scopus 로고    scopus 로고
    • On the Bayes-risk consistency of regularized boosting methods
    • Lugosi, G., Vayatis, N.: On the Bayes-risk consistency of regularized boosting methods. Ann. Statist. 32(1), 30-55 (2004)
    • (2004) Ann. Statist , vol.32 , Issue.1 , pp. 30-55
    • Lugosi, G.1    Vayatis, N.2
  • 27
    • 0007259908 scopus 로고    scopus 로고
    • Topics in Non-parametric Statistics, Ecole d'été de Probabilités de Saint-Flour 1998
    • Springer, Heidelberg
    • Nemirovski, A.: Topics in Non-parametric Statistics, Ecole d'été de Probabilités de Saint-Flour 1998. Lecture Notes in Mathematics, vol. 1738. Springer, Heidelberg (2000)
    • (2000) Lecture Notes in Mathematics , vol.1738
    • Nemirovski, A.1
  • 29
    • 9444226947 scopus 로고    scopus 로고
    • Optimal rates of aggregation
    • Schölkopf, B, Warmuth, M, eds, Computational Learning Theory and Kernel Machines, Springer, Heidelberg
    • Tsybakov, A.B.: Optimal rates of aggregation. In: Schölkopf, B., Warmuth, M. (eds.) Computational Learning Theory and Kernel Machines. LNCS (LNAI), vol. 2777, pp. 303-313. Springer, Heidelberg (2003)
    • (2003) LNCS (LNAI , vol.2777 , pp. 303-313
    • Tsybakov, A.B.1
  • 30
    • 3142725508 scopus 로고    scopus 로고
    • Optimal aggregation of classifiers in statistical learning
    • Tsybakov, A.B.: Optimal aggregation of classifiers in statistical learning. Ann. Statist. 32(1), 135-166 (2004)
    • (2004) Ann. Statist , vol.32 , Issue.1 , pp. 135-166
    • Tsybakov, A.B.1
  • 31
    • 0041548213 scopus 로고
    • Necessary and sufficient conditions for the uniform convergence of empirical means to their true values
    • Vapnik, V.N., Chervonenkis, A.Y.: Necessary and sufficient conditions for the uniform convergence of empirical means to their true values. Teor. Veroyatn. Primen. 26, 543-563 (1981)
    • (1981) Teor. Veroyatn. Primen , vol.26 , pp. 543-563
    • Vapnik, V.N.1    Chervonenkis, A.Y.2
  • 33
    • 0034410225 scopus 로고    scopus 로고
    • Mixing strategies for density estimation
    • Yang, Y.: Mixing strategies for density estimation. Ann. Statist. 28(1), 75-87 (2000)
    • (2000) Ann. Statist , vol.28 , Issue.1 , pp. 75-87
    • Yang, Y.1
  • 34
    • 4644257995 scopus 로고    scopus 로고
    • Statistical behavior and consistency of classification methods based on convex risk minimization
    • Zhang, T.: Statistical behavior and consistency of classification methods based on convex risk minimization. Ann. Statist. 32(1), 56-85 (2004)
    • (2004) Ann. Statist , vol.32 , Issue.1 , pp. 56-85
    • Zhang, T.1
  • 35
    • 0347607206 scopus 로고    scopus 로고
    • Adaptive estimation in Pattern Recognition by combining different procedures
    • Zhang, T.: Adaptive estimation in Pattern Recognition by combining different procedures. Statistica Sinica 10, 1069-1089 (2000)
    • (2000) Statistica Sinica , vol.10 , pp. 1069-1089
    • Zhang, T.1


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