25 search results - page 2 / 5 » Graph Mining with Variational Dirichlet Process Mixture Mode... |
ECML
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
KDD
2010
ACM
13 years 2 months ago
2010
ACM
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
JCB
2007
13 years 4 months ago
2007
The problem of inferring haplotypes from genotypes of single nucleotide polymorphisms (SNPs) is essential for the understanding of genetic variation within and among populations, ...
ICDM
2007
IEEE
13 years 11 months ago
2007
IEEE
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...