Simple in-network data aggregation (or fusion) techniques for sensor networks have been the focus of several recent research efforts, but they are insufficient to support advance...
Rajnish Kumar, Matthew Wolenetz, Bikash Agarwalla,...
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
In previous work, we presented a tight approximate response-time analysis for tasks with offsets. While providing a tight bound on response times, the tight analysis exhibits simi...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Analysis of materials obtained from physical simulations is important in the physical sciences. Our research was motivated by the need to investigate the properties of a simulated...
Attila G. Gyulassy, Mark A. Duchaineau, Vijay Na...