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Are Few Bins Enough: Testing Histogram Distributions

Summary: Test whether a distribution over [n] is a k-histogram (piecewise-constant on ≤k contiguous intervals) vs ε-far in ℓ1 with a new sample- and time-efficient tester. Provides a nearly-matching information-theoretic sample lower bound, substantially tightening prior bounds (Indyk et al.; Canonne et al.). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1668
Venue
PODS
Year
2016
Pagerank
5.093636e-05
Overall Rank
12,024 | 17.51%
DOI
10.1145/2902251.2902274

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Authors

BibTeX Citation

@inproceedings{canonne_pods16,
        address = {New York, NY, USA},
        series = {{PODS} '16},
        title = {{Are Few Bins Enough: Testing Histogram Distributions}},
        url = {https://dl.acm.org/doi/10.1145/2902251.2902274},
        doi = {10.1145/2902251.2902274},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Canonne, Clément L.},
        year = {2016}
}

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13,381 Corrigendum: Are Few Bins Enough: Testing Histogram Distributions 2023 PODS -
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