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» Approximate Frequency Counts over Data Streams
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AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
15 years 3 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
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...
VLDB
2005
ACM
196views Database» more  VLDB 2005»
15 years 3 months ago
Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling
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...
Graham Cormode, S. Muthukrishnan, Irina Rozenbaum
ICDE
2008
IEEE
139views Database» more  ICDE 2008»
15 years 11 months ago
Simultaneous Equation Systems for Query Processing on Continuous-Time Data Streams
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...
Jennie Rogers, Olga Papaemmanouil, Ugur Çet...
PODS
2009
ACM
110views Database» more  PODS 2009»
15 years 10 months ago
Optimal tracking of distributed heavy hitters and quantiles
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...
Ke Yi, Qin Zhang
86
Voted
ICC
2007
IEEE
15 years 4 months ago
Soft Estimation of Time-Varying Frequency Selective Channels Using Kalman Smoothing
— 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...
Valery Ramon, Cédric Herzet, Xavier Wautele...