Advances in Probabilistic Graphical Models
Gamez, Jose A. (Ed.)
Sold by Anybook.com, Lincoln, United Kingdom
AbeBooks Seller since 22 December 1999
Used - Hardcover
Condition: Used - Good
Quantity: 1 available
Add to basketSold by Anybook.com, Lincoln, United Kingdom
AbeBooks Seller since 22 December 1999
Condition: Used - Good
Quantity: 1 available
Add to basketThis is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9783540689942.
Seller Inventory # 4148764
In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;
contributions to the area are coming from computer science, mathematics, statistics and engineering.
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional
independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;
contributions to the area are coming from computer science, mathematics, statistics and engineering.
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional
independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
"About this title" may belong to another edition of this title.
Anybook Ltd is a company registered in England and Wales. Company Registration Number: 3692291. VAT Number: GB753406145. Share Capital GBP100.
Registered Offices:
28 West End,
Burgh le Marsh,
Lincolnshire,
PE24 5EY
UK
Customer Services:
2,Outer Circle Business Park,
Outer Circle Road,
Lincoln
LN2 4HX
UK
Email Address: sales@anybook.com
Telephone Number: +44 (0) 1522 519 991
Authorized Representative: Ms. Claire Williams
Orders usually ship within 1 business day. We use Royal Mail and other reputable couriers at greatly discounted postage rates. If your book order is heavy or over-sized, or valuable enough to require tracking, we may contact you to let you know extra shipping is required.
Order quantity | 3 to 6 business days | 2 to 4 business days |
---|---|---|
First item | £ 4.48 | £ 5.36 |
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.