ON THE OPTIMALITY OF SAMPLE-BASED ESTIMATES OF THE EXPECTATION OF THE EMPIRICAL MINIMIZER ∗, ∗∗
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[1] P. Massart,et al. Risk bounds for statistical learning , 2007, math/0702683.
[2] M. Rudelson,et al. Combinatorics of random processes and sections of convex bodies , 2004, math/0404192.
[3] P. Massart. Some applications of concentration inequalities to statistics , 2000 .
[4] Shahar Mendelson,et al. A Few Notes on Statistical Learning Theory , 2002, Machine Learning Summer School.
[5] Gilles Blanchard,et al. On the Rate of Convergence of Regularized Boosting Classifiers , 2003, J. Mach. Learn. Res..
[6] O. Bousquet. Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms , 2002 .
[7] S. Geer. A New Approach to Least-Squares Estimation, with Applications , 1986 .
[8] M. Ledoux. The concentration of measure phenomenon , 2001 .
[9] M. Talagrand. New concentration inequalities in product spaces , 1996 .
[10] S. Geer,et al. Adaptivity of Support Vector Machines with ` 1 Penalty , 2004 .
[11] V. Koltchinskii. Local Rademacher complexities and oracle inequalities in risk minimization , 2006, 0708.0083.
[12] G. Lugosi,et al. On the Bayes-risk consistency of regularized boosting methods , 2003 .
[13] Jon A. Wellner,et al. Weak Convergence and Empirical Processes: With Applications to Statistics , 1996 .
[14] Thierry Klein. Une inégalité de concentration à gauche pour les processus empiriques , 2002 .
[15] E. Rio,et al. Inégalités de concentration pour les processus empiriques de classes de parties , 2001 .
[16] S. R. Jammalamadaka,et al. Empirical Processes in M-Estimation , 2001 .
[17] P. Bartlett,et al. Local Rademacher complexities , 2005, math/0508275.
[18] Shahar Mendelson,et al. Improving the sample complexity using global data , 2002, IEEE Trans. Inf. Theory.
[19] Philip D. Plowright,et al. Convexity , 2019, Optimization for Chemical and Biochemical Engineering.
[20] P. MassartLedoux. Concentration Inequalities Using the Entropy Method , 2002 .
[21] A. W. van der Vaart,et al. Uniform Central Limit Theorems , 2001 .
[22] Vladimir Vapnik,et al. Chervonenkis: On the uniform convergence of relative frequencies of events to their probabilities , 1971 .
[23] P. Bartlett,et al. Empirical minimization , 2006 .
[24] David Haussler,et al. Sphere Packing Numbers for Subsets of the Boolean n-Cube with Bounded Vapnik-Chervonenkis Dimension , 1995, J. Comb. Theory, Ser. A.
[25] G. Lugosi,et al. Complexity regularization via localized random penalties , 2004, math/0410091.
[26] Michael I. Jordan,et al. Convexity, Classification, and Risk Bounds , 2006 .
[27] A. Tsybakov,et al. Optimal aggregation of classifiers in statistical learning , 2003 .
[28] M. Talagrand. Sharper Bounds for Gaussian and Empirical Processes , 1994 .
[29] Peter L. Bartlett,et al. The Importance of Convexity in Learning with Squared Loss , 1998, IEEE Trans. Inf. Theory.
[30] V. Koltchinskii. Rejoinder: Local Rademacher complexities and oracle inequalities in risk minimization , 2006, 0708.0135.
[31] V. Koltchinskii,et al. Rademacher Processes and Bounding the Risk of Function Learning , 2004, math/0405338.
[32] Peter L. Bartlett,et al. Classification with a Reject Option using a Hinge Loss , 2008, J. Mach. Learn. Res..
[33] P. Massart,et al. About the constants in Talagrand's concentration inequalities for empirical processes , 2000 .