Abstract. We tackle the problem of new users or documents in collaborative filtering. Generalization over users by grouping them into user groups is beneficial when a rating is t...
We study the problem of statistical model checking of probabilistic systems for PCTL unbounded until property P1p(ϕ1 U ϕ2) (where 1 ∈ {<, ≤, >, ≥}) using the computa...
Ru He, Paul Jennings, Samik Basu, Arka P. Ghosh, H...
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...
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...