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Towards an Axiomatization of Statistical Privacy and Utility

Summary: Axiomatic framework for statistical privacy and utility under randomized algorithms, characterizing their interaction and guiding mechanism design. Identifies a class of differential-privacy relaxations and argues DP outputs are best interpreted as graphs rather than query answers or synthetic data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1515
Venue
PODS
Year
2010
Pagerank
6.3743594e-05
Overall Rank
4,189 | 70.86%
DOI
-

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