Consistency of Learning Processes

  • Vladimir N. Vapnik


The goal of this part of the theory is to describe the conceptual model for learning processes that are based on the Empirical Risk Minimization inductive principle. This part of the theory has to explain when a learning machine that minimizes empirical risk can achieve a small value of actual risk (can generalize) and when it can not. In other words, the goal of this part is to describe the necessary and sufficient conditions for the consistency of learning processes that minimizes the empirical risk.


Probability Measure Indicator Function Uniform Convergence Elementary Event Inductive Inference 
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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