The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Background: In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interact...
Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an...
Stephanie Lindsey, Cauligi S. Raghavendra, Krishna...
We use a constrained optimization framework to derive fundamental scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structure...