Abstract-- We investigate the problem of clustering on distributed data streams. In particular, we consider the k-median clustering on stream data arriving at distributed sites whi...
Abstract-- Large graph datasets are common in many emerging database applications, and most notably in large-scale scientific applications. To fully exploit the wealth of informati...
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit in...
— Approximating the sum of Log–Normal random variables (RVs) is a long–standing open issue, in the old and recent literature, and many approaches have been proposed to deal w...
Marco Di Renzo, Fabio Graziosi, Fortunato Santucci