Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
In this paper we survey two multi-dimensional Scale Saliency approaches based on graphs and the k-d partition algorithm. In the latter case we introduce a new divergence metric an...
: Efficient information sharing is very important for emergency and rescue operations. These operations often have to be performed in environments where no communication infrastruc...
— Cluster Ensembles is a framework for combining multiple partitionings obtained from separate clustering runs into a final consensus clustering. This framework has attracted mu...
This work addresses the issue of design optimization for faulttolerant hard real-time systems. In particular, our focus is on the handling of transient faults using both checkpoin...
Petru Eles, Viacheslav Izosimov, Paul Pop, Zebo Pe...