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Bayesian Reasoning and Machine Learning

ISBN-10: 0521518148
ISBN-13: 9780521518147
Edition: 2011
Authors: David Barber
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Book details

List price: $97.95
Copyright year: 2011
Publisher: Cambridge University Press
Publication date: 2/2/2012
Binding: Hardcover
Pages: 720
Size: 7.75" wide x 10.00" long x 1.50" tall
Weight: 3.498
Language: English

David Barber is a Reader in Information Processing at University College London.

Preface
Inference in Probabilistic Models
Probabilistic reasoning
Basic graph concepts
Belief networks
Graphical models
Efficient inference in trees
The junction tree algorithm
Making decisions
Learning in Probabilistic Models
Statistics for machine learning
Learning as inference
Naive Bayes
Learning with hidden variables
Bayesian model selection
Machine Learning
Machine learning concepts
Nearest neighbour classification
Unsupervised linear dimension reduction
Supervised linear dimension reduction
Linear models
Bayesian linear models
Gaussian processes
Mixture models
Latent linear models
Latent ability models
Dynamical Models
Discrete-state Markov models
Continuous-state Markov models
Switching linear dynamical systems
Distributed computation
Approximate Inference
Sampling
Deterministic approximate inference
Appendix. Background mathematics
Bibliography
Index

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