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Differentially Private Data Generation with Missing Data
Summary: Formalizes DP synthetic-data generation with missing values and proposes three adaptive strategies that markedly improve utility across diverse missingness regimes. Models missingness as a sampling process to derive tighter bounds relating DP guarantees on incomplete inputs to privacy of the true complete data.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13436
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 4.7180617e-05
- Overall Rank
- 7,485 | 47.93%
- DOI
-
10.14778/3659437.3659455
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 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 |
0.00053933811 |
| 111 |
Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release |
2007 |
PODS |
0.00047073785 |
| 453 |
Towards Practical Differential Privacy for SQL Queries |
2018 |
VLDB |
0.00022741848 |
| 1,446 |
PrivBayes: Private Data Release via Bayesian Networks |
2014 |
SIGMOD |
0.0001194108 |
| 1,738 |
PrivateSQL: A Differentially Private SQL Query Engine |
2019 |
VLDB |
0.00010720057 |
| 1,764 |
PriView: Practical Differentially Private Release of Marginal Contingency Tables |
2014 |
SIGMOD |
0.00010636626 |
| 3,329 |
AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data |
2022 |
VLDB |
7.2156424e-05 |
| 3,831 |
Kamino: Constraint-Aware Differentially Private Data Synthesis |
2021 |
VLDB |
6.7181688e-05 |
| 4,252 |
DPSynthesizer: Differentially Private Data Synthesizer for Privacy Preserving Data Sharing |
2014 |
VLDB |
6.3233894e-05 |
| 4,668 |
PrivateClean: Data Cleaning and Differential Privacy |
2016 |
SIGMOD |
6.0115918e-05 |
| 6,065 |
APEx: Accuracy-Aware Differentially Private Data Exploration |
2019 |
SIGMOD |
5.2291685e-05 |
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| 11,143 |
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| 3,304 |
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