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Controlling the Generalization Ability of Learning Processes

  • Vladimir N. Vapnik
Chapter
Part of the Statistics for Engineering and Information Science book series (ISS)

Abstract

The theory for controlling the generalization ability of learning machines is devoted to constructing an inductive principle for minimizing the risk functional using a small sample of training instances.

Keywords

Generalization Ability Minimum Description Length Admissible Function Empirical Risk Structural 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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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Vladimir N. Vapnik
    • 1
  1. 1.Room 3-130AT&T Labs-ResearchRed BankUSA

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