Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Activator-inhibitor models have been widely used to explain several morphogenetic processes. They have also been used to engineer algorithms for computer graphics, distributed syst...
We are interested in finding natural communities in largescale linked networks. Our ultimate goal is to track changes over time in such communities. For such temporal tracking, we...
John E. Hopcroft, Omar Khan, Brian Kulis, Bart Sel...
In this paper, we propose an on-demand distributed clustering algorithm for multi-hop packet radio networks. These types of networks, also known as ad hoc networks, are dynamic in ...