Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
: In this paper, we develop a framework for the modeling, analysis, and computation of solutions to multitiered financial network problems with intermediaries in which both the sou...
Earth mover's distance (EMD for short) is a perceptually meaningful dissimilarity measure between histograms. The computation of EMD reduces to a network flow optimization pro...
A high-performance data-path to implement DSP kernels is proposed in this paper. The data-path is based on a flexible, universal, and regular component to optimally exploiting both...
Michalis D. Galanis, George Theodoridis, Spyros Tr...