We consider bit communication complexity of binary consensus in synchronous message passing systems with processes prone to crashes. A distributed algorithm is locally scalable wh...
— We present a Graph-based method for low-level segmentation of unfiltered 3D data. The core of this approach is based on the construction of a local neighborhood structure and ...
— Centrality is a concept often used in social network analysis to study different properties of networks that are modeled as graphs. We present a new centrality metric called Lo...
The communities of a social network are sets of vertices with more connections inside the set than outside. We theoretically demonstrate that two commonly observed properties of s...
Many conceptual studies of local cortical networks assume completely random wiring. For spatially extended networks, however, such random graph models are inadequate. The geometry...