The amount of graph-structured data has recently experienced an enormous growth in many
applications. To transform such data into useful information, fast analytics algorithms and …

Community detection is an important research area in social networks analysis where we
are concerned with discovering the structure of the social network. Detecting communities is …

The surging traffic volumes and dynamic user mobility patterns pose great challenges for
cellular network operators to reduce operational costs and ensure service quality. Cloud …

The amount of graph-structured data has recently experienced an enormous growth in many
applications. To transform such data into useful information, high-performance analytics …

Given an underlying graph, we consider the following dynamics: Initially, each node locally
chooses a value in {-1,1\}, uniformly at random and independently of other nodes. Then, in …

The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of
nodes into two blocks while minimizing the weight sum of the cut edges. Here, we introduce …

Inspired by the increasing interest in self-organizing social opportunistic networks, we
investigate the problem of distributed detection of unknown communities in dynamic random …

We investigate the behavior of a simple majority dynamics on networks of agents whose
interaction topology exhibits a community structure. By leveraging recent advancements in …

The most commonly used method to tackle the graph partitioning problem in practice is the
multilevel metaheuristic. In this paper we introduce size-constrained label propagation …

Spectral techniques have proved amongst the most effective approaches to graph
clustering. However, in general they require explicit computation of the main eigenvectors of …