Variational Bayesian Learning Theory

Language: English

Published by Cambridge University Press, 2025

1107430763 / 9781107430761

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this book summarizes recent developments in the non-asymptotic and asymptotic theory of variational Bayesian learning and suggests how this theory can be applied in practice. The authors begin by developing a basic framework with a focus on conjugacy, which enables the reader to derive tractable algorithms. Next, it summarizes non-asymptotic theory, which, although limited in application to bilinear models, precisely describes the behavior of the variational Bayesian solution and reveals its sparsity inducing mechanism. Finally, the text summarizes asymptotic theory, which reveals phase transition phenomena depending on the prior setting, thus providing suggestions on how to set hyperparameters for particular purposes. Detailed derivations allow readers to follow along without prior knowledge of the mathematical techniques specific to Bayesian learning.…

Seller Inventory # 9781107430761

Title
Variational Bayesian Learning Theory
Author
Shinichi Nakajima
Publisher
Cambridge University Press
Publication year
2025
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1107430763
ISBN 13
9781107430761
Item weight
898 grams
Dimensions
229x152x33 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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