DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms

Summary: DP-PQD privately determines, for each count, sum, or median predicate query, whether black-box synthetic data answers lie within a user-specified error threshold of the private source. It supplies differential privacy despite no generator-level guarantees. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 13931
Venue: VLDB
Year: 2024
Pagerank: 5.093636e-05
Overall Rank: 11,349 | 22.14%
DOI: 10.14778/3617838.3617844

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Shweta Patwa (Duke University)
2. Danyu Sun (Duke University)
3. Amir Gilad (Hebrew University)
4. Ashwin Machanavajjhala (Duke University)
5. Sudeepa Roy (Duke University)

BibTeX Citation

@article{patwa_vldb24,
        title = {{DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms}},
        author = {Patwa, Shweta and Sun, Danyu and Gilad, Amir and Machanavajjhala, Ashwin and Roy, Sudeepa},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {1},
        pages = {65--78},
        doi = {10.14778/3617838.3617844},
        url = {https://doi.org/10.14778/3617838.3617844},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,786	Computing Inconsistency Measures Under Differential Privacy	2025	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
611	Optimizing Linear Counting Queries Under Differential Privacy	2010	PODS	0.00015747402
2,012	Understanding the Sparse Vector Technique for Differential Privacy	2017	VLDB	9.3073552e-05
2,129	Data Synthesis based on Generative Adversarial Networks	2018	VLDB	9.1266572e-05
2,167	Optimizing error of high-dimensional statistical queries under differential privacy	2018	VLDB	9.047803e-05
2,476	Data Synthesis via Differentially Private Markov Random Fields	2021	VLDB	8.5258582e-05
2,841	AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data	2022	VLDB	8.0637668e-05
3,412	Kamino: Constraint-Aware Differentially Private Data Synthesis	2021	VLDB	7.4344343e-05
4,394	R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys	2022	SIGMOD	6.7274063e-05
5,566	Differential Privacy and the US Census	2019	PODS	6.1712366e-05
7,924	PSynDB: Accurate and Accessible Private Data Generation	2019	VLDB	5.5181056e-05

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