Graphical models for machine learning and digital communication / Brendan J. Frey.

Format:

Book

Author/Creator:

Frey, Brendan J., author.

Series:

Adaptive computation and machine learning

Language:

English

Subjects (All):

Digital communications.

Graph theory.

Machine learning.

Physical Description:

1 online resource (xiii, 195 pages) : illustrations.

Other Title:

MIT Press CogNet.

Place of Publication:

Cambridge, Massachusetts : The MIT Press, [1998]

System Details:

text file

Summary:

A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graph-based inference techniques to develop new algorithms. Among the algorithms described are the wake-sleep algorithm for unsupervised learning, the iterative turbodecoding algorithm (currently the best error-correcting decoding algorithm), the bits-back coding method, the Markov chain Monte Carlo technique, and variational inference.

Notes:

"A Bradford book."

Includes bibliographical references (pages 179-189) and index.

Description based on print version record.

Other Format:

Print version: Frey, Brendan J. Graphical models for machine learning and digital communication.

ISBN:

9780262273206

0262273209

Access Restriction:

Restricted for use by site license.