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Personalized Truncation for Personalized Privacy

Summary: Proposes a PDP personalized truncation mechanism for counting and sum estimation. Theoretically, it matches or beats prior PDP methods up to polylog factors and gains in favorable cases; experiments show empirical advantages and applicability to user-level DP for SJA queries under foreign-key constraints. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6995
Venue
SIGMOD
Year
2024
Pagerank
4.1945683e-05
Overall Rank
10,992 | 23.54%
DOI
10.1145/3698825

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Rank Citing Paper Year Venue Pagerank
10,041 A General Framework for Per-record Differential Privacy 2026 SIGMOD 4.1945683e-05
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