Controlling the Generalization Ability of Learning Processes

  • Vladimir N. Vapnik

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 Asymptotic Rate 
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 1995

Authors and Affiliations

  • Vladimir N. Vapnik
    • 1
  1. 1.AT&T Bell LaboratoriesHolmdelUSA

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