Controlling the Generalization Ability of Learning Processes

Vladimir N. Vapnik
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Vladimir N. Vapnik: AT&T Bell Laboratories

Chapter Chapter 4 in The Nature of Statistical Learning Theory, 1995, pp 89-118 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 1995
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-2440-0_5

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DOI: 10.1007/978-1-4757-2440-0_5

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