Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
—In this paper, we develop an analytical framework which explains the emergence of superpeer networks on execution of the commercial peer-to-peer bootstrapping protocols by incom...
Emerging applications in sensor systems and network-wide IP traffic analysis present many technical challenges. They need distributed monitoring and continuous tracking of events....
Networks of ultra-low-power nodes capable of sensing, computation, and wireless communication have applications in medicine, science, industrial automation, and security. Over the...
A fundamental problem in data management is to draw a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With large, streamin...
Graham Cormode, S. Muthukrishnan, Ke Yi, Qin Zhang