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PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy
Summary: PriPL-Tree: hierarchical LDP structure that models node distributions with piecewise-linear fits instead of the usual uniform-within-partition assumption, improving range-query accuracy with few segments. Multidimensional extension uses data-aware adaptive grids built from PriPL marginals.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13521
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 4.358174e-05
- Overall Rank
- 9,290 | 35.44%
- DOI
-
10.14778/3681954.3681981
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 178 |
Boosting the Accuracy of Differentially Private Histograms Through Consistency |
2010 |
VLDB |
0.00037726596 |
| 714 |
Understanding Hierarchical Methods for Differentially Private Histograms |
2013 |
VLDB |
0.00017670757 |
| 844 |
The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds |
2020 |
VLDB |
0.00015964123 |
| 1,365 |
FITing-Tree: A Data-aware Index Structure |
2019 |
SIGMOD |
0.00012379754 |
| 1,516 |
PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions |
2016 |
SIGMOD |
0.00011558246 |
| 1,762 |
PriView: Practical Differentially Private Release of Marginal Contingency Tables |
2014 |
SIGMOD |
0.00010629368 |
| 1,928 |
A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy |
2014 |
VLDB |
0.00010062105 |
| 1,935 |
Marginal Release Under Local Differential Privacy |
2018 |
SIGMOD |
0.00010033955 |
| 2,108 |
LISA: A Learned Index Structure for Spatial Data |
2020 |
SIGMOD |
9.5283642e-05 |
| 2,141 |
Online Piece-wise Linear Approximation of Numerical Streams with Precision Guarantees* |
2009 |
VLDB |
9.4561227e-05 |
| 2,408 |
Estimating Numerical Distributions under Local Differential Privacy |
2020 |
SIGMOD |
8.8694564e-05 |
| 2,556 |
Answering Multi-Dimensional Analytical Queries under Local Differential Privacy |
2019 |
SIGMOD |
8.5485513e-05 |
| 3,136 |
FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems |
2022 |
VLDB |
7.4926368e-05 |
| 3,361 |
Answering Multi-Dimensional Range Queries under Local Differential Privacy |
2021 |
VLDB |
7.1718964e-05 |
| 3,401 |
Answering Range Queries Under Local Differential Privacy |
2019 |
VLDB |
7.1343786e-05 |
| 7,034 |
A Neural Database for Differentially Private Spatial Range Queries |
2022 |
VLDB |
4.8504321e-05 |
| 7,471 |
A workload-adaptive mechanism for linear queries under local differential privacy |
2020 |
VLDB |
4.7158603e-05 |
| 11,246 |
Trajectory Data Collection with Local Differential Privacy |
2023 |
VLDB |
4.1905499e-05 |
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