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Maximum Entropy and Bayesian Methods

Santa Barbara, California, U.S.A., 1993

  • Glenn R. Heidbreder

Part of the Fundamental Theories of Physics book series (FTPH, volume 62)

Table of contents

  1. Front Matter
    Pages i-x
  2. Tutorial

  3. Bayesian Hyperparameters

    1. David J. C. MacKay
      Pages 43-59
    2. David H. Wolpert, Charlie E. M. Strauss
      Pages 61-78
    3. David H. Wolpert
      Pages 79-86
  4. Bayesian Robustness

    1. Carlos C. Rodríguez
      Pages 87-96
    2. Sanjib Basu, Sreenivasa Rao Jammalamadaka, Wei Liu
      Pages 97-106
  5. Clustering

  6. Inverse Problems

    1. Ali Mohammad-Djafari, Jérôme Idier
      Pages 121-134
    2. Enders A. Robinson
      Pages 135-147
  7. Quantum Probability Theory

    1. Timothy C. Wallstrom
      Pages 149-155
    2. Timothy C. Wallstrom
      Pages 157-159
    3. R. N. Silver, T. Wallstrom, H. F. Martz
      Pages 161-174
  8. Philosophy

    1. Anthony J. M. Garrett
      Pages 175-186
  9. Computational Issues

    1. Paul Desmedt, Ignace Lemahieu, K. Thielemans
      Pages 197-203
    2. Paul Desmedt, Ignace Lemahieu, Koen Bastiaens
      Pages 205-211
    3. Koen Bastiaens, Paul Desmedt, Ignace Lemahieu
      Pages 213-219
  10. Applications

    1. K. M. Hanson, D. R. Wolf
      Pages 255-263
    2. R. C. Puetter, R. K. Piña
      Pages 275-292
    3. Peter Cheeseman, Bob Kanefsky, Richard Kraft, John Stutz, Robin Hanson
      Pages 293-308
    4. Andrew G. Green, David J. C. MacKay
      Pages 309-318
    5. John E. Tansley, Martin J. Oldfield, David J. C. MacKay
      Pages 319-325
    6. Nielson W. Schulenburg
      Pages 327-338
    7. W. von der Linden, M. Donath, V. Dose
      Pages 343-350
    8. Nina T. Plotkin, Abraham J. Wyner
      Pages 351-363
    9. Laurence Mailaender, Ronald A. Iltis
      Pages 365-374
    10. Michael Stutzer
      Pages 375-390
    11. G. A. Vignaux, Bernard Robertson
      Pages 391-399
  11. Back Matter
    Pages 409-414

About this book

Introduction

Maximum entropy and Bayesian methods have fundamental, central roles in scientific inference, and, with the growing availability of computer power, are being successfully applied in an increasing number of applications in many disciplines. This volume contains selected papers presented at the Thirteenth International Workshop on Maximum Entropy and Bayesian Methods. It includes an extensive tutorial section, and a variety of contributions detailing application in the physical sciences, engineering, law, and economics.
Audience: Researchers and other professionals whose work requires the application of practical statistical inference.

Keywords

Estimator algorithms bayesian methods classification clustering communication genetic algorithms microelectromechanical system (MEMS)

Editors and affiliations

  • Glenn R. Heidbreder
    • 1
  1. 1.Department of Electrical and Computer EngineeringUniversity of California, Santa BarbaraSanta BarbaraUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8729-7
  • Copyright Information Springer Science+Business Media B.V. 1996
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4407-5
  • Online ISBN 978-94-015-8729-7
  • Buy this book on publisher's site