Bayesian learning techniques: Application to neural networks with constraints on weight space

A. Eleuteri; R. Tagliaferri; L. Milano; F. Acernese; M. De Laurentiis

Bayesian learning techniques: Application to neural networks with constraints on weight space

A. Eleuteri, R. Tagliaferri, L. Milano, F. Acernese, M. De Laurentiis

Istituto Nazionale Tumori Fondazione G. Pascale

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	216-232
Number of pages	17
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2486 LNCS
Publication status	Published - 2002

Keywords

Bayesian learning frameworks
Learning with constraints
Survival analysis

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

Cite this

Bayesian learning techniques : Application to neural networks with constraints on weight space. / Eleuteri, A.; Tagliaferri, R.; Milano, L. et al.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2486 LNCS, 2002, p. 216-232.

Research output: Contribution to journal › Article › peer-review

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KW - Survival analysis

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Bayesian learning techniques: Application to neural networks with constraints on weight space

Abstract

Keywords

ASJC Scopus subject areas

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