Sinossi
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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Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)
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Hardcover. Condizione: Good. No Jacket. Missing dust jacket; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Codice articolo G026206202XI3N01
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Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)
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Adaptive Computation and Machine Learning: Graphical Models for Machine Learning and Digital Communication
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Condizione: Good. This 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. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9780262062022. Codice articolo 2323970
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