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Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling

Summary: Formalizes inverse-distribution streaming, showing forward-distribution sketches can fail for frequency-of-frequencies queries. Introduces dynamic inverse sampling with provable space, time, and accuracy guarantees for quantiles, histograms, heavy hitters, and rare-item detection. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
9498
Venue
VLDB
Year
2005
Pagerank
9.1271562e-05
Overall Rank
2,128 | 85.41%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{cormode_vldb05,
        title = {{Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling}},
        author = {Cormode, Graham and Muthukrishnan, S. and Rozenbaum, Irina},
        journal = {PVLDB},
        series = {{VLDB} '05},
        volume = {31},
        pages = {25--36},
        year = {2005}
}

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