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Bayesian Learning Techniques: Application to Neural Networks with Constraints on Weight Space

  • A. Eleuteri
  • R. Tagliaferri
  • L. Milano
  • F. Acernese
  • M. De Laurentiis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2486)

Abstract

In this paper the fundamentals of Bayesian learning techniques are shown, and their application to neural network modeling is illustrated. Furthermore, it is shown how constraints on weight space can easily be embedded in a Bayesian framework. Finally, the application of these techniques to a complex neural network model for survival analysis is used as a significant example.

Keywords

Bayesian learning frameworks Learning with constraints Survival analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • A. Eleuteri
    • 1
  • R. Tagliaferri
    • 2
    • 3
  • L. Milano
    • 4
  • F. Acernese
    • 4
  • M. De Laurentiis
    • 5
  1. 1.Dipartimento di Matematica ed Applicazioni “R. Caccioppoli”Universita di Napoli “Federico II” Napoli, and INFN sez. NapoliNapoliItalia
  2. 2.DMIUniversitá di SalernoBaronissi, SaItalia
  3. 3.INFM unitá di SalernoItalia
  4. 4.Dipartimento di Scienze FisicheUniversitá di Napoli “Federico II” and INFN sez.NapoliNapoliItalia
  5. 5.Dipartimento di Endocrinologia ed Oncologia Molecolare e ClinicaUniversitá di Napoli “Federico II”NapoliItalia

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