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Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy
Summary: Introduces a holistic mechanism for answering multiple relational queries under differential privacy, outperforming standard composition in error as the query count grows. Delivers theoretical optimality and practical gains, notably on skewed data and large d.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6627
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 4.7258659e-05
- Overall Rank
- 7,437 | 48.32%
- DOI
-
10.1145/3589268
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 7,441 |
Continual Observation of Joins under Differential Privacy |
2024 |
SIGMOD |
4.7251588e-05 |
| 8,520 |
Differentially Private Hierarchical Heavy Hitters |
2024 |
PODS |
4.4893996e-05 |
| 10,041 |
A General Framework for Per-record Differential Privacy |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,094 |
N2E: A General Framework to Reduce Node-Differential Privacy to Edge-Differential Privacy for Graph Analytics |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,494 |
Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,995 |
Personalized Truncation for Personalized Privacy |
2024 |
SIGMOD |
4.1905499e-05 |
| 11,077 |
Confidence Intervals for Private Query Processing |
2024 |
VLDB |
4.1905499e-05 |
| 11,115 |
DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System |
2024 |
VLDB |
4.1905499e-05 |
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.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 83 |
Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis |
2009 |
SIGMOD |
0.00053910987 |
| 111 |
Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release |
2007 |
PODS |
0.00047047599 |
| 178 |
Boosting the Accuracy of Differentially Private Histograms Through Consistency |
2010 |
VLDB |
0.00037726596 |
| 451 |
Towards Practical Differential Privacy for SQL Queries |
2018 |
VLDB |
0.00022807098 |
| 642 |
Private Analysis of Graph Structure |
2011 |
VLDB |
0.00018757732 |
| 714 |
Understanding Hierarchical Methods for Differentially Private Histograms |
2013 |
VLDB |
0.00017670757 |
| 1,177 |
Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins |
2013 |
SIGMOD |
0.00013465351 |
| 1,607 |
Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets |
2014 |
VLDB |
0.00011171719 |
| 1,740 |
PrivateSQL: A Differentially Private SQL Query Engine |
2019 |
VLDB |
0.00010696383 |
| 1,762 |
PriView: Practical Differentially Private Release of Marginal Contingency Tables |
2014 |
SIGMOD |
0.00010629368 |
| 2,686 |
Private Release of Graph Statistics using Ladder Functions |
2015 |
SIGMOD |
8.31087e-05 |
| 3,083 |
Computing Local Sensitivities of Counting Queries with Joins |
2020 |
SIGMOD |
7.5985351e-05 |
| 5,499 |
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys |
2022 |
SIGMOD |
5.4737427e-05 |
| 7,059 |
Residual Sensitivity for Differentially Private Multi-Way Joins |
2021 |
SIGMOD |
4.8404261e-05 |
| 7,584 |
A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries |
2022 |
PODS |
4.7015411e-05 |
| 11,166 |
Universal Private Estimators |
2023 |
PODS |
4.1905499e-05 |
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