The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the foll...
Detecting communities in real world networks is an important problem for data analysis in science and engineering. By clustering nodes intelligently, a recursive algorithm is desig...
Crowdsourcing is an effective tool to solve hard tasks. By bringing 100,000s of people to work on simple tasks that only humans can do, we can go far beyond traditional models of ...
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Over the past decade, there has been great interest in the study of buffer management policies in the context of packet transmission for network switches. In a typical model, a sw...