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PrivRM: A Framework for Range Mean Estimation under Local Differential Privacy

Summary: PrivRM provides a framework for private range-mean estimation under local differential privacy. It yields two adaptable implementations (PrivRMI, PrivRM*) adaptable to numerical perturbation mechanisms and a distribution-aware AA strategy to tighten perturbation on skewed data, achieving notable accuracy gains over prior LDP methods under identical privacy budgets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7302
Venue
SIGMOD
Year
2025
Pagerank
4.3441378e-05
Overall Rank
9,393 | 34.66%
DOI
10.1145/3725414

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10,153 Defense against Poisoning Attacks under Shuffle-DP 2026 SIGMOD 4.1945683e-05
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