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Check Availability Lawrence Library / Main Collection: QA279.5 .K65 2009Library Info

Author LinkKoller, Daphne.
Title LinkProbabilistic graphical models : principles and techniques / Daphne Koller and Nir Friedman.
Imprint Cambridge, MA : MIT Press, c2009.
Description xxxv, 1231 p. :  ill. ;  24 cm.
Type of Material Book
Series ( Adaptive computation and machine learning )
Series ( Adaptive computation and machine learning.)
Bibliography Note Includes bibliographical references (p. [1171]-1207) and indexes.
Contents 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.
Subject LinkGraphical modeling (Statistics)
LinkBayesian statistical decision theory -- Graphic methods.
Add.Author LinkFriedman, Nir.

System Number 000678673
ISBN Link9780262013192 (hardcover : alk. paper)
Link0262013193 (hardcover : alk. paper)

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