TY - GEN

T1 - Bayesian networks on dirichlet distributed vectors

AU - Buntine, Wray

AU - Du, Lan

AU - Nurmi, Petteri

PY - 2010

Y1 - 2010

N2 - Exact Bayesian network inference exists for Gaussian and multinomial distributions. For other kinds of distributions, approximations or restrictions on the kind of inference done are needed. In this paper we present generalized networks of Dirichlet distributions, and show how, using the two-parameter Poisson-Dirichlet distribution and Gibbs sampling, one can do approximate inference over them. This involves integrating out the probability vectors but leaving auxiliary discrete count vectors in their place. We illustrate the technique by extending standard topic models to "structured" documents, where the document structure is given by a Bayesian network of Dirichlets.

AB - Exact Bayesian network inference exists for Gaussian and multinomial distributions. For other kinds of distributions, approximations or restrictions on the kind of inference done are needed. In this paper we present generalized networks of Dirichlet distributions, and show how, using the two-parameter Poisson-Dirichlet distribution and Gibbs sampling, one can do approximate inference over them. This involves integrating out the probability vectors but leaving auxiliary discrete count vectors in their place. We illustrate the technique by extending standard topic models to "structured" documents, where the document structure is given by a Bayesian network of Dirichlets.

UR - http://www.scopus.com/inward/record.url?scp=80052416805&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9789526033143

T3 - Proceedings of the 5th European Workshop on Probabilistic Graphical Models, PGM 2010

SP - 33

EP - 40

BT - Proceedings of the 5th European Workshop on Probabilistic Graphical Models, PGM 2010

T2 - 5th European Workshop on Probabilistic Graphical Models, PGM 2010

Y2 - 13 September 2010 through 15 September 2010

ER -