—Individuals in social networks are often organized under some hierarchy such as a command structure. In many cases, when this structure is unknown, there is a need to discover h...
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
Abstract-- We consider distributed parameter estimation using quantized observations in wireless sensor networks where due to bandwidth constraint, each sensor quantizes its local ...
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...