: Sensor management deals with the efficient resource allocation to meet mission objectives of the application, air traffic control. A schedule for the sensors is constructed, whic...
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
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 propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
This paper addresses the problem of tracking and diagnosing complex systems with mixtures of discrete and continuous variables. This problem is a difficult one, particularly when ...
Uri Lerner, Ronald Parr, Daphne Koller, Gautam Bis...