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Innovations in Bayesian Networks

Theory and Applications

  • Dawn E. Holmes
  • Lakhmi C. Jain

Part of the Studies in Computational Intelligence book series (SCI, volume 156)

Table of contents

  1. Front Matter
    Pages I-X
  2. Dawn E. Holmes, Lakhmi C. Jain
    Pages 1-5
  3. Richard E. Neapolitan
    Pages 7-32
  4. David Heckerman
    Pages 33-82
  5. Kevin B. Korb, Ann E. Nicholson
    Pages 83-116
  6. Sylvia Nagl, Matt Williams, Jon Williamson
    Pages 131-167
  7. Xia Jiang, Michael M. Wagner, Gregory F. Cooper
    Pages 169-185
  8. Philippe Leray, Stijn Meganek, Sam Maes, Bernard Manderick
    Pages 219-249
  9. M. Julia Flores, José A. Gámez, Serafín Moral
    Pages 251-280
  10. Dawn E. Holmes
    Pages 281-288
  11. Rodrigo de Salvo Braz, Eyal Amir, Dan Roth
    Pages 289-317
  12. Back Matter
    Pages 319-321

About this book

Introduction

Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained.

Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.

Keywords

Bayesian Networks Bayesian network Learning Bayesian networks Topologie artificial intelligence computational intelligence intelligence learning modeling statistics system modeling

Editors and affiliations

  • Dawn E. Holmes
    • 1
  • Lakhmi C. Jain
    • 2
  1. 1.Department of Statistics and Applied ProbabilityUniversity of CaliforniaSanta BarbaraUSA
  2. 2.University of South Australia AdelaideMawson LakesAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-85066-3
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-85065-6
  • Online ISBN 978-3-540-85066-3
  • Series Print ISSN 1860-949X
  • Buy this book on publisher's site