Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Abstract. Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically se...
This paper concerns automatic hardware synthesis from data flow graph (DFG) specification in system level design. In the presented design methodology, each node of a data flow gra...
We give a graph decomposition technique that creates entirely independent subproblems for graph problems such as coloring and dominating sets that can be solved without synchroniz...