Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
We present a Bayesian approach to color constancy which utilizes a nonGaussian probabilistic model of the image formation process. The parameters of this model are estimated direc...
Charles R. Rosenberg, Thomas P. Minka, Alok Ladsar...
Abstract-- We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic...
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
Image matching is an essential task in many computer vision applications. It is obvious that thorough utilization of all available information is critical for the success of match...