Answering Multi-Dimensional Range Queries under Local Differential Privacy
Summary: Local differential privacy for multi-dimensional range queries; introduces Two-Dimensional Grids (TDG) that partition 2-D attribute domains into grids to answer all 2-D ranges and extrapolate to higher dimensions. To overcome loss of fine-grained information, Hybrid-Dimensional Grids (HDG) combines 1-D and 2-D grids with a principled granularity guideline, yielding substantial accuracy gains over prior approaches on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jianyu Yang (Beijing Institute of Technology; Purdue University)
- 2. Tianhao Wang (Purdue University)
- 3. Ninghui Li (Purdue University)
- 4. Xiang Cheng (Beijing Institute of Technology)
- 5. Sen Su (Beijing Institute of Technology)
BibTeX Citation
@article{yang_vldb21,
title = {{Answering Multi-Dimensional Range Queries under Local Differential Privacy}},
author = {Yang, Jianyu and Wang, Tianhao and Li, Ninghui and Cheng, Xiang and Su, Sen},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {3},
pages = {378--390},
doi = {10.14778/3430915.3430927},
url = {https://doi.org/10.14778/3430915.3430927},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,417 | Towards Practical Oblivious Join | 2022 | SIGMOD | 8.6061949e-05 |
| 5,439 | Improving Utility and Security of the Shuffler-based Differential Privacy | 2020 | VLDB | 6.2188088e-05 |
| 6,951 | RM2: Answer Counting Queries Efficiently under Shuffle Differential Privacy | 2025 | SIGMOD | 5.7303405e-05 |
| 7,503 | Disclosure-Compliant Query Answering | 2024 | SIGMOD | 5.6029996e-05 |
| 9,300 | PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy | 2024 | VLDB | 5.289545e-05 |
| 10,610 | A Workload-Aware Encrypted Index for Efficient Privacy-Preserving Range Queries | 2026 | VLDB | 5.093636e-05 |
| 11,462 | Federated Calibration and Evaluation of Binary Classifiers | 2023 | VLDB | 5.093636e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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