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Answering Range Queries Under Local Differential Privacy

Summary: Study of answering 1-dimensional range count queries under Local Differential Privacy (LDP). Develops methods to estimate interval fractions under LDP, enabling privacy-preserving range statistics and downstream quantile computations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5695
Venue
SIGMOD
Year
2019
Pagerank
7.589057e-05
Overall Rank
3,260 | 77.64%
DOI
10.1145/3299869.3300102

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BibTeX Citation

@inproceedings{kulkarni_sigmod19,
        title = {{Answering Range Queries Under Local Differential Privacy}},
        author = {Kulkarni, Tejas},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3300102},
        url = {https://dl.acm.org/doi/10.1145/3299869.3300102},
        year = {2019}
}

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