A General Framework for Per-record Differential Privacy
Summary: General method to convert DP mechanisms to PrDP whose error depends on the dataset's minimum per-record budget, not the global minimum. Introduces privacy-specified domain partitioning and query augmentation (local DP) to privately estimate that minimum; produces first PrDP count/sum/max algorithms with much better utility than PDP. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Xinghe Chen
- 2. Dajun Sun
- 3. Quanqing Xu
- 4. Wei Dong
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