We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Given a spatio-temporal network (ST network) whose edge properties vary with time, a time-sub-interval minimum spanning tree (TSMST) is a collection of distinct minimum spanning t...
One way to improve inferences on sensor data is to tune the algorithms through a time-consuming offline procedure. A less expensive, and potentially more accurate method is to use...
Ezekiel S. Bhasker, Steven W. Brown, William G. Gr...
We describe a practical vision of ubiquitous computing with tangible interfaces, that orbits around an individual and is mediated by his or her personal consumer electronic device...
Abstract. A localization algorithm using radio interferometric measurements is presented. A probabilistic model is constructed that accounts for general noise models and lends itse...
Dennis Lucarelli, Anshu Saksena, Ryan Farrell, I-J...