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Variational Bayes for generic topic models

: Heinrich, Gregor; Goesele, Michael


Mertsching, B.:
KI 2009: Advances in artificial intelligence. 32nd Annual German Conference on AI : Paderborn, Germany, September 15-18, 2009; Proceedings
Berlin: Springer, 2009 (Lecture Notes in Artificial Intelligence 5803)
ISBN: 978-3-642-04616-2
ISBN: 3-642-04616-9
ISSN: 0302-9743
Annual Conference on Artificial Intelligence <32, 2009, Paderborn>
Conference Paper
Fraunhofer IGD ()
artificial intelligence (AI); machine learning; topic model

The article contributes a derivation of variational Bayes for a large class of topic models by generalising from the well-known model of latent Dirichlet allocation. For an abstraction of these models as systems of interconnected mixtures, variational update equations are obtained, leading to inference algorithms for models that so far have used Gibbs sampling exclusively.