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Computational Learning Theory

  • Miroslav Kubat
Chapter

Abstract

As they say, nothing is more practical than a good theory. And indeed, mathematical models of learnability have helped improve our understanding of what it takes to induce a useful classifier from data, and, conversely, why the outcome of a machine-learning undertaking so often disappoints. And so, even though this textbook does not want to be mathematical, it cannot help introducing at least the basic concepts of the computational learning theory.

References

  1. 6.
    Blumer, W., Ehrenfeucht, A., Haussler, D., & Warmuth, M. K. (1989). Learnability and the Vapnik-Chervonenkis dimension. Journals of the ACM, 36, 929–965.MathSciNetCrossRefzbMATHGoogle Scholar
  2. 18.
    Cover, T. M. (1965). Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition. IEEE Transactions on Electronic Computers, EC-14, 326–334.CrossRefzbMATHGoogle Scholar
  3. 41.
    Kearns, M. J. & Vazirani, U. V. (1994). An introduction to computational learning theory. Cambridge, MA: MIT Press.Google Scholar
  4. 86.
    Shawe-Taylor, J., Anthony, M., & Biggs, N. (1993). Bounding sample size with the Vapnik-Chervonenkis dimension. Discrete Applied Mthematics, 42(1), 65–73.MathSciNetCrossRefzbMATHGoogle Scholar
  5. 91.
    Valiant, L. G. (1984). A theory of the learnable. Communications of the ACM, 27, 1134–1142.CrossRefzbMATHGoogle Scholar
  6. 92.
    Vapnik, V. N. (1992). Estimation of dependences based on empirical data. New York: Springer.zbMATHGoogle Scholar
  7. 94.
    Vapnik, V. N. & Chervonenkis, A. Y. (1971). On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications, 16, 264–280.CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Miroslav Kubat
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of MiamiCoral GablesUSA

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