Variational Bayesian Learning Theory
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Language: en
Pages: 561
Pages: 561
Type: BOOK - Published: 2019-07-11 - Publisher: Cambridge University Press
This introduction to the theory of variational Bayesian learning summarizes recent developments and suggests practical applications.
Language: en
Pages: 561
Pages: 561
Type: BOOK - Published: 2019-07-11 - Publisher: Cambridge University Press
Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this b
Language: en
Pages: 241
Pages: 241
Type: BOOK - Published: 2006-03-30 - Publisher: Springer Science & Business Media
Treating VB approximation in signal processing, this monograph is for academic and industrial research groups in signal processing, data analysis, machine learn
Language: en
Pages: 295
Pages: 295
Type: BOOK - Published: 2009-08-13 - Publisher: Cambridge University Press
Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular
Language: en
Pages: 502
Pages: 502
Type: BOOK - Published: 2005-09-26 - Publisher: Springer Science & Business Media
This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005.
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