APEx: Accuracy-Aware Differentially Private Data Exploration
Summary: APEx enables accuracy-aware, DP-driven data exploration with adaptive queries and accuracy bounds. It translates queries and bounds into DP algorithms with low privacy loss, guaranteeing accuracy and end-to-end DP proofs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chang Ge (University of Waterloo)
- 2. Xi He (University of Waterloo)
- 3. Ihab F. Ilyas (University of Waterloo)
- 4. Ashwin Machanavajjhala (Duke University)
BibTeX Citation
@inproceedings{ge_sigmod19,
title = {{APEx: Accuracy-Aware Differentially Private Data Exploration}},
author = {Ge, Chang and He, Xi and Ilyas, Ihab F. and Machanavajjhala, Ashwin},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3300092},
url = {https://dl.acm.org/doi/10.1145/3299869.3300092},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,504 | A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy | 2014 | VLDB |
| 2 | 62 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD |
| 3 | 10,313 | Differentially Private Explanations for Clusters | 2026 | SIGMOD |
| 4 | 9,604 | Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements | 2021 | SIGMOD |
| 5 | 281 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB |
| 6 | 1,144 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB |
| 7 | 2,108 | An Adaptive Mechanism for Accurate Query Answering under Differential Privacy | 2012 | VLDB |
| 8 | 11,480 | Explaining Differentially Private Query Results With DPXPlain | 2023 | VLDB |
| 9 | 8,719 | DPXPlain: Privately Explaining Aggregate Query Answers | 2023 | VLDB |
| 10 | 8,843 | Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration | 2023 | VLDB |