Many self-organizing and self-adaptive systems use the biologically inspired “gradient” primitive, in which each device in a network estimates its distance to the closest devi...
Jonathan Bachrach, Jacob Beal, Joshua Horowitz, Da...
The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classi...
In this paper an algorithm based on the ensemble empirical mode decomposition (EEMD) is presented. The key idea on the EEMD relies on averaging the modes obtained by EMD applied t...
The Uncapacitated Facility Location Problem (UFLP) is one of the most widely studied discrete location problems, whose applications arise in a variety of settings. We tackle the U...
In this paper, we present a theoretical analysis of the error with three basic Monte Carlo radiosity algorithms, based on continuous collision shooting random walks, discrete coll...