An instance of the path hitting problem consists of two families of paths, D and H, in a common undirected graph, where each path in H is associated with a non-negative cost. We r...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
Many large-scale networks such as ad hoc and sensor networks, peer-to-peer networks, or the Internet have the property that the number of independent nodes does not grow arbitrari...
Detecting and counting the number of copies of certain subgraphs (also known as network motifs or graphlets), is motivated by applications in a variety of areas ranging from Biolo...
We study the complexity and the I/O-efficient computation of flow on triangulated terrains. We present an acyclic graph, the descent graph, that enables us to trace flow paths in ...
Mark de Berg, Otfried Cheong, Herman J. Haverkort,...