A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference i...
We present a probabilistic topic model for jointly identifying properties and attributes of social media review snippets. Our model simultaneously learns a set of properties of a ...
This paper is about a novel rule-based approach for reasoning about qualitative spatiotemporal relations among technology-rich autonomous objects, to which we refer to as artifact...
Pervasive computing environments introduce new requirements in expressiveness and flexibility of access control policies which are almost addressable leveraging contextual informa...
Amir Reza Masoumzadeh, Morteza Amini, Rasool Jalil...