We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of t...
This paper explores probabilistic lexico-syntactic pattern matching, also known as soft pattern matching. While previous methods in soft pattern matching are ad hoc in computing t...
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
Stochastic models such as hidden Markov models or stochastic context free grammars can fail to return the correct, maximum likelihood solution in the case of semantic ambiguity. T...