Graph transformation works under a whole-world assumption. In modelling realistic systems, this typically makes for large graphs and sometimes also large, hard to understand rules....
Many applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). In our previous work, we proposed a ...
Abstract. Discovery of evolving regions in large graphs is an important issue because it is the basis of many applications such as spam websites detection in the Web, community lif...
Abstract - Streaming applications are often implemented as task graphs. Currently, techniques exist to derive buffer capacities that guarantee satisfaction of a throughput constrai...
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...