With the increasing popularity of largescale probabilistic graphical models, even "lightweight" approximate inference methods are becoming infeasible. Fortunately, often...
The protein inference problem represents a major challenge in shotgun proteomics. Here we describe a novel Bayesian approach to address this challenge that incorporates the predict...
Yong Fuga Li, Randy J. Arnold, Yixue Li, Predrag R...
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations, which relies on a simple probabilistic model and assumes no manual coding. W...
We present an action recognition method based on the concept of reliable inference. Our approach is formulated in a probabilistic framework using posterior class ratios to verify ...
The purpose of this paper is to compare different ways of adopting reason-maintenance techniques in incremental parsing (and interpretation). A reasonmaintenance system supports i...