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Frequency Moments in Noisy Streaming and Distributed Data under Mismatch Ambiguity

Summary: Introduces Fp-mismatch-ambiguity, a data-dependent parameter enabling sublinear-space streaming and communication for estimating ground-truth frequency moments from noisy data, with tight lower bounds. Noise makes F2 polynomial-space and generally rules out input-size-independent polylog communication. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
2031
Venue
PODS
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,156 | 30.33%
DOI
10.1145/3801901

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BibTeX Citation

@inproceedings{liu_pods26,
        address = {New York, NY, USA},
        series = {{PODS} '26},
        title = {{Frequency Moments in Noisy Streaming and Distributed Data under Mismatch Ambiguity}},
        url = {https://dl.acm.org/doi/10.1145/3801901},
        doi = {10.1145/3801901},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Liu, Kaiwen and Zhang, Qin},
        year = {2026}
}

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