14 search results - page 1 / 3 » Hybrid Variational Gibbs Collapsed Inference in Topic Models |
UAI
2008
13 years 5 months ago
2008
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
NIPS
2007
13 years 5 months ago
2007
A wide variety of Dirichlet-multinomial ‘topic’ models have found interesting applications in recent years. While Gibbs sampling remains an important method of inference in su...
NIPS
2008
13 years 5 months ago
2008
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
KI
2009
Springer
13 years 10 months ago
2009
Springer
The article contributes a derivation of variational Bayes for a large class of topic models by generalising from the well-known model of latent Dirichcation. For an abstraction of ...
PKDD
2009
Springer
13 years 10 months ago
2009
Springer
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...