The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such ...
Bogdan Georgescu, Xiang Sean Zhou, Dorin Comaniciu...
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...