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Graphical Models for Machine Learning and Digital Communication

Type doc. :

Livre

Langue :

Anglais

Auteur(s) :

Frey, Brendan J.

Editeur(s) :

The Mit Press

Année d'édition :

1998

Sujet(s):
machine learning
digital communication

Thème :

Informatique

ISBN :

9780262062022
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Afficher le Résumé

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.

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N° Bulletin Date / Année de parution Titre N° Spécial Sommaire
N° d'Exemplaire / inventaire Cote Localisation Type de Support Type de Prêt Statut Date de Restitution Prévue Réservation
178716A02 004 FRE 8 C 1 BIB-Centrale / Ouvrages Papier interne disponible
Frey, B. (1998). Graphical Models for Machine Learning and Digital Communication . The Mit Press;