Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Profiling Internet backbone traffic is becoming an increasingly hard problem since users and applications are avoiding detection using traffic obfuscation and encryption. The key ...
Marios Iliofotou, Brian Gallagher, Tina Eliassi-Ra...
Data association (obtaining correspondences) is a ubiquitous problem in computer vision. It appears when matching image features across multiple images, matching image features to ...
Inspired by the recent interest in combining geometry with random graph models, we explore in this paper two generalizations of the random dot product graph model proposed by Kraet...