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Bias-Aware Sketches

Summary: Introduces bias-aware linear sketches that account for systematic coordinate bias, avoiding the large tail-mass errors that undermine standard sketches. Proves strictly stronger guarantees and validates practical gains on real and synthetic distributed/streaming workloads. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11776
Venue
VLDB
Year
2017
Pagerank
5.3914428e-05
Overall Rank
8,653 | 40.64%
DOI
10.14778/3099622.3099624

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{chen_vldb17,
        title = {{Bias-Aware Sketches}},
        author = {Chen, Jiecao and Zhang, Qin},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {9},
        pages = {961--972},
        doi = {10.14778/3099622.3099624},
        url = {https://doi.org/10.14778/3099622.3099624},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,036 On-Off Sketch: A Fast and Accurate Sketch on Persistence 2021 VLDB 5.7212447e-05
8,204 PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees 2025 SIGMOD 5.4667903e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

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