We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
Supporting scalable and efficient routing and service provision in Mobile Ad Hoc Networks (MANET) has been a big research challenge. Conventional topology-based unicast and multic...
The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge th...
A scalable and expressive peer-to-peer (P2P) networking and computing framework requires efficient resource discovery services. Here we propose NEVRLATE, for Network-Efficient V...
Ajay Chander, Steven Dawson, Patrick Lincoln, Davi...