Modeling and Reasoning with Bayesian Networks
- Author: Adnan Darwiche, University of California, Los Angeles
- Date Published: August 2014
- availability: Available
- format: Paperback
- isbn: 9781107678422
Paperback
Other available formats:
Hardback, eBook
Looking for an inspection copy?
This title is not currently available on inspection
-
This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.
Read more- Assumes very little background, making it ideal for students and researchers new to the field
- Provides extensive coverage of modelling techniques and algorithms for both exact and approximate inference
- An in-depth treatment of the underlying theory, perfect as a springboard for further research
Reviews & endorsements
'… both practical and advanced … The first five chapters are sufficient for students and practitioners to gain the necessary knowledge in order to build Bayesian networks for moderately sized applications with the aid of a software tool … All major inference methods are covered in later chapters which allow researchers and software developers to implement their own software systems tailored to their needs … It is a comprehensive book that can be used for self study by students and newcomers to the field or as a companion for courses on probabilistic reasoning. Experienced researchers may also find deeper information on some topics. In my opinion, the book should definitely be [on] the bookshelf of everyone who teaches Bayesian networks and builds probabilistic reasoning agents.' Artificial Intelligence
See more reviews'[This] book will make an excellent textbook; it covers topics suitable for both undergraduate and graduate courses. It will also help practitioners get a firm grasp of the fundamentals of modeling and inference with BNs, as well as some recent advances.' ACM Computing Reviews
Customer reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity
×Product details
- Date Published: August 2014
- format: Paperback
- isbn: 9781107678422
- length: 562 pages
- dimensions: 254 x 178 x 29 mm
- weight: 0.96kg
- contains: 246 b/w illus. 64 tables 342 exercises
- availability: Available
Table of Contents
1. Introduction
2. Propositional logic
3. Probability calculus
4. Bayesian networks
5. Building Bayesian networks
6. Inference by variable elimination
7. Inference by factor elimination
8. Inference by conditioning
9. Models for graph decomposition
10. Most likely instantiations
11. The complexity of probabilistic inference
12. Compiling Bayesian networks
13. Inference with local structure
14. Approximate inference by belief propagation
15. Approximate inference by stochastic sampling
16. Sensitivity analysis
17. Learning: the maximum likelihood approach
18. Learning: the Bayesian approach
Appendix A: notation
Appendix B: concepts from information theory
Appendix C: fixed point iterative methods
Appendix D: constrained optimization.
Related Books
related journals
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email [email protected]
Register Sign in» Proceed
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.
Continue ×Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.
×