Bayesian graphical models are commonly used to build student models from data. A number of standard algorithms are available to train Bayesian models from student skills assessment...
Michel C. Desmarais, Alejandro Villarreal, Michel ...
This paper presents a judgement and decision making analysis of collaborative problem solving. This analysis is done with respect to the Raven and CoRaven decision-making tools fo...
David C. Wilkins, Patricia M. Jones, Roger Bargar,...
We show how to nd a minimum weight loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the rst step in the method of conditioning for inference....
We propose statistical data association techniques for visual tracking of enormously large numbers of objects. We do not assume any prior knowledge about the numbers involved, and...
Margrit Betke, Diane E. Hirsh, Angshuman Bagchi, N...
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...