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» Sketching Sampled Data Streams
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ICDE
2009
IEEE
174views Database» more  ICDE 2009»
12 years 3 months ago
Sketching Sampled Data Streams
—Sampling is used as a universal method to reduce the running time of computations – the computation is performed on a much smaller sample and then the result is scaled to comp...
Florin Rusu, Alin Dobra
PODS
2007
ACM
225views Database» more  PODS 2007»
12 years 8 months ago
Sketching unaggregated data streams for subpopulation-size queries
IP packet streams consist of multiple interleaving IP flows. Statistical summaries of these streams, collected for different measurement periods, are used for characterization of ...
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carste...
VLDB
2005
ACM
196views Database» more  VLDB 2005»
12 years 1 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
NIPS
2008
11 years 9 months ago
One sketch for all: Theory and Application of Conditional Random Sampling
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Ping Li, Kenneth Ward Church, Trevor Hastie
PVLDB
2008
116views more  PVLDB 2008»
11 years 7 months ago
Tighter estimation using bottom k sketches
Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a ...
Edith Cohen, Haim Kaplan
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