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Examples of Excess Risk Bounds in Prediction Problems

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Part of the Lecture Notes in Mathematics book series (LNMECOLE,volume 2033)

Abstract

Empirical risk minimization with convex loss was studied in detail by Blanchard 324 et al. [26] and Bartlett et al. [16]. In the last paper, rather subtle bounds relating 325 excess risks with respect to a “surrogate” convex loss and with respect to the binary 326 classification loss were also studied. Earlier, Zhang [154] provided initial versions 327 of such bounds.

Keywords

  • Loss Function
  • Excess Risk
  • Prediction Problem
  • Reproduce Kernel Hilbert Space
  • Empirical Risk Minimization

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Vladimir Koltchinskii .

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© 2011 Springer-Verlag Berlin Heidelberg

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Koltchinskii, V. (2011). Examples of Excess Risk Bounds in Prediction Problems. In: Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems. Lecture Notes in Mathematics(), vol 2033. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22147-7_5

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