In many clustering applications, the user has some vague notion of the number and membership of the desired clusters. However, it is difficult for the user to provide such knowled...
Anil K. Jain, Pavan Kumar Mallapragada, Martin H. ...
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
We present two parallel algorithms and their Unified Parallel C implementations for Bayesian indoor positioning systems. Our approaches are founded on Markov Chain Monte Carlo si...
An algorithm has been developed for the detection of point targets in uncluttered background based on a Bayesian track before detect method. The algorithm has an application in th...
We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from co...
Eugene Grois, William H. Hsu, Mikhail Voloshin, Da...