Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
We introduce Pulse, a framework for processing continuous queries over models of continuous-time data, which can compactly and accurately represent many real-world activities and p...
We consider the the problem of tracking heavy hitters and quantiles in the distributed streaming model. The heavy hitters and quantiles are two important statistics for characteri...
— This paper addresses soft estimation of time-varying frequency selective channels using Kalman smoothing. The proposed estimator uses soft extrinsic information provided by a c...