Exploring Privacy-Accuracy Tradeoffs using DPComp
Summary: DPComp: a web-based demo of privacy-accuracy tradeoffs under differential privacy. Analysts can compare DP algorithms, inspect outputs to quantify error, and contribute new algorithms or datasets to an evolving benchmark under Hay et al.'s methodology. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Michael Hay (Colgate University)
- 2. Ashwin Machanavajjhala (Duke University)
- 3. Gerome Miklau (University of Massachusetts Amherst)
- 4. Yan Chen (Duke University)
- 5. Dan Zhang (University of Massachusetts Amherst)
- 6. George Bissias (University of Massachusetts Amherst)
BibTeX Citation
@inproceedings{hay_sigmod16,
title = {{Exploring Privacy-Accuracy Tradeoffs using DPComp}},
author = {Hay, Michael and Machanavajjhala, Ashwin and Miklau, Gerome and Chen, Yan and Zhang, Dan and Bissias, George},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2899387},
url = {https://dl.acm.org/doi/10.1145/2882903.2899387},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,338 | DPGraph: A Benchmark Platform for Differentially Private Graph Analysis | 2021 | SIGMOD | 5.6393827e-05 |
| 7,968 | Optimizing Fitness-For-Use of Differentially Private Linear Queries | 2021 | VLDB | 5.516666e-05 |
| 8,203 | SAP HANA goes private – From Privacy Research to Privacy Aware Enterprise Analytics | 2019 | VLDB | 5.4670416e-05 |
| 11,026 | PrivEval: a tool for interactive evaluation of privacy metrics in synthetic data generation | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,300 | Principled Evaluation of Differentially Private Algorithms using DPBench | 2016 | SIGMOD | 8.7833594e-05 |
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