Differentially Private Data Release over Multiple Tables
Summary: Algorithm for differentially private synthetic data answering multiple linear queries over multi-table databases, tackling join-induced sensitivity amplification that breaks single-table approaches. Proves parameterized lower bounds (near-optimal up to logs) and adds hierarchical-join partitioning using "uniformized sensitivities" to boost utility. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Badih Ghazi (Google)
- 2. Xiao Hu (Google; University of Waterloo)
- 3. Ravi Kumar (Google)
- 4. Pasin Manurangsi (Google)
BibTeX Citation
@inproceedings{ghazi_pods23,
address = {New York, NY, USA},
series = {{PODS} '23},
title = {{Differentially Private Data Release over Multiple Tables}},
url = {https://dl.acm.org/doi/10.1145/3584372.3588665},
doi = {10.1145/3584372.3588665},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Ghazi, Badih and Hu, Xiao and Kumar, Ravi and Manurangsi, Pasin},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,376 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 5.893174e-05 |
| 10,775 | PrivPetal: Relational Data Synthesis via Permutation Relations | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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