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Space-Efficient Estimation of Statistics over Sub-Sampled Streams

Summary: Characterizes space-efficient estimation of original-stream statistics (frequency moments, support size, entropy, heavy hitters) when only sub-sampled stream observations are available. Presents algorithms with matching upper and lower bounds that tightly characterize space complexity. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1583
Venue
PODS
Year
2012
Pagerank
5.093636e-05
Overall Rank
12,305 | 15.58%
DOI
10.1145/2213556.2213594

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Authors

BibTeX Citation

@inproceedings{mcgregor_pods12,
        address = {New York, NY, USA},
        series = {{PODS} '12},
        title = {{Space-Efficient Estimation of Statistics over Sub-Sampled Streams}},
        url = {https://dl.acm.org/doi/10.1145/2213556.2213594},
        doi = {10.1145/2213556.2213594},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {McGregor, Andrew and Pavan, A. and Tirthapura, Srikanta and Woodruff, David P.},
        year = {2012}
}

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Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
288 Towards Estimation Error Guarantees for Distinct Values 2000 PODS 0.00022296371
2,697 Sketching Probabilistic Data Streams 2007 SIGMOD 8.2451054e-05
2,988 Estimating Statistical Aggregates on Probabilistic Data Streams 2007 PODS 7.8907087e-05
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