t ion which is much more abstract than a place vocabulary, the kinematic topology. Kinematic topology does not define qualitative inference rules, but provides a characterization o...
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
Consider mobile targets moving in a plane and their movements being monitored by a network such as a field of sensors. We develop distributed algorithms for in-network tracking an...
We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multiinterval offline task scheduling to minimize power usage. Here each proce...
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...