Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy
Summary: Introduces the Low-Rank Mechanism (LRM), using low-rank workload approximation to make batch query answering under differential privacy practical and accurate. It approaches the theoretical lower bound and substantially outperforms matrix-mechanism and naive baselines. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ganzhao Yuan (South China University of Technology)
- 2. Zhenjie Zhang (Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd.)
- 3. Marianne Winslett (Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd.; University of Illinois Urbana-Champaign)
- 4. Xiaokui Xiao (Nanyang Technological University)
- 5. Yin Yang (Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd.)
- 6. Zhifeng Hao (South China University of Technology)
BibTeX Citation
@article{yuan_vldb12,
title = {{Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy}},
author = {Yuan, Ganzhao and Zhang, Zhenjie and Winslett, Marianne and Xiao, Xiaokui and Yang, Yin and Hao, Zhifeng},
journal = {PVLDB},
series = {{VLDB} '12},
volume = {5},
number = {11},
pages = {1352--1363},
doi = {10.14778/2350229.2350254},
url = {https://doi.org/10.14778/2350229.2350254},
year = {2012}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 121 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.00031639377 |
| 123 | Revealing Information while Preserving Privacy | 2003 | PODS | 0.00031082693 |
| 611 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00015747402 |
| 757 | Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption | 2010 | SIGMOD | 0.00014306168 |
| 775 | Differentially Private Data Cubes: Optimizing Noise Sources and Consistency | 2011 | SIGMOD | 0.00014110531 |
| 2,799 | iReduct: Differential Privacy with Reduced Relative Errors | 2011 | SIGMOD | 8.1125988e-05 |
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|---|---|---|---|---|
| 1 | 9,545 | PrivRM: A Framework for Range Mean Estimation under Local Differential Privacy | 2025 | SIGMOD |
| 2 | 4,132 | Answering Multi-Dimensional Range Queries under Local Differential Privacy | 2021 | VLDB |
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| 4 | 9,602 | Answering Private Linear Queries Adaptively using the Common Mechanism | 2023 | VLDB |
| 5 | 6,951 | RM2: Answer Counting Queries Efficiently under Shuffle Differential Privacy | 2025 | SIGMOD |
| 6 | 2,167 | Optimizing error of high-dimensional statistical queries under differential privacy | 2018 | VLDB |
| 7 | 2,108 | An Adaptive Mechanism for Accurate Query Answering under Differential Privacy | 2012 | VLDB |
| 8 | 7,898 | A workload-adaptive mechanism for linear queries under local differential privacy | 2020 | VLDB |
| 9 | 1,504 | A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy | 2014 | VLDB |
| 10 | 611 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS |