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Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)

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Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning) Cover

 

Synopses & Reviews

Publisher Comments:

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.

Product Details

ISBN:
9780262062022
Author:
Frey, Brendan J.
Publisher:
Bradford Book
Location:
Cambridge, Mass :
Subject:
Computer Science
Subject:
Graphic Methods
Subject:
Digital communications
Subject:
Artificial Intelligence
Subject:
Graph theory
Subject:
Machine Theory
Subject:
Machine learning
Subject:
Artificial Intelligence - General
Subject:
Intelligence (AI) & Semantics
Subject:
Computers-Reference - General
Series:
Adaptive Computation and Machine Learning series Graphical Models for Machine Learning and Digital
Publication Date:
19980731
Binding:
HARDCOVER
Grade Level:
from 17
Language:
English
Illustrations:
Y
Pages:
211
Dimensions:
9 x 6.2 x 0.8 in

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