KI 2009: Advances in Artificial Intelligence

Volume 5803 of the series Lecture Notes in Computer Science pp 161-168

Variational Bayes for Generic Topic Models

  • Gregor HeinrichAffiliated withFraunhofer IGD and University of Leipzig
  • , Michael GoeseleAffiliated withTU Darmstadt

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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.