We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Preference elicitation (PE) is an important component of interactive decision support systems that aim to make optimal recommendations to users by actively querying their preferen...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...