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Cover Art
PRINTED BOOKS
Author Koller, Daphne.

Title Probabilistic graphical models : principles and techniques / Daphne Koller and Nir Friedman.

Published Cambridge, MA : MIT Press, [2009]
©2009

Copies

Location Call No. Status
 UniM ERC  519.5420285 KOLL    AVAILABLE
 UniM ERC  519.5420285 KOLL    AVAILABLE
Physical description xxxv, 1233 pages : illustrations ; 24 cm.
Series Adaptive computation and machine learning.
Adaptive computation and machine learning.
Bibliography Includes bibliographical references (pages [1173]-1209) and indexes.
Contents 1. Introduction -- 2. Foundations -- I. Representation -- 3. Bayesian Network Representation -- 4. Undirected Graphical Models -- 5. Local Probabilistic Models -- 6. Template-Based Representations -- 7. Gaussian Network Models -- 8. Exponential Family -- II. Inference -- 9. Exact Inference: Variable Elimination -- 10. Exact Inference: Clique Trees -- 11. Inference as Optimization -- 12. Particle-Based Approximate Inference -- 13. MAP Inference -- 14. Inference in Hybrid Networks -- 15. Inference in Temporal Models -- III. Learning -- 16. Learning Graphical Models: Overview -- 17. Parameter Estimation -- 18. Structure Learning in Bayesian Networks -- 19. Partially Observed Data -- 20. Learning Undirected Models -- IV. Actions and Decisions -- 21. Causality -- 22. Utilities and Decisions -- 23. Structured Decision Problems -- 24. Epilogue -- A. Background Material.
Other author Friedman, Nir.
Subject Graphical modeling (Statistics)
Bayesian statistical decision theory -- Graphic methods.
ISBN 9780262013192 (hardcover : alk. paper)
0262013193 (hardcover : alk. paper)