Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fie...
V. Chandrasekaran, Jason K. Johnson, Alan S. Wills...
Determining where a given sensor is physically located is a challenging issue. In this paper, we address the localization problem where, initially, a certain number of sensors cal...
Abstract— We consider a distributed multi-agent network system where the goal is to minimize an objective function that can be written as the sum of component functions, each of ...
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...