Practical Differential Privacy via Grouping and Smoothing
Summary: GS pre-processes one-time, non-overlapping counts by grouping and smoothing (averaging) to lower sensitivity before epsilon-DP noise. A sampling-guided grouping mechanism minimizes smoothing perturbation, enabling low-noise DP and real-data superiority over competitors, with extensive experiments. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Georgios Kellaris (Hong Kong University of Science and Technology)
- 2. Stavros Papadopoulos (Hong Kong University of Science and Technology)
BibTeX Citation
@article{kellaris_vldb13,
title = {{Practical Differential Privacy via Grouping and Smoothing}},
author = {Kellaris, Georgios and Papadopoulos, Stavros},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {5},
doi = {10.14778/2535573.2488337},
url = {https://doi.org/10.14778/2535573.2488337},
year = {2013}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,841 | Publishing Graph Degree Distribution with Node Differential Privacy | 2016 | SIGMOD | 9.5270124e-05 |
| 6,232 | The Fast and the Private: Task-based Dataset Search | 2024 | CIDR | 5.8417106e-05 |
| 6,339 | A Neural Approach to Spatio-Temporal Data Release with User-Level Differential Privacy | 2023 | SIGMOD | 5.8072694e-05 |
| 7,564 | Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures | 2023 | VLDB | 5.4938591e-05 |
| 8,139 | Optimizing Fitness-For-Use of Differentially Private Linear Queries | 2021 | VLDB | 5.3905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 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 | 0.0003107472 |
| 347 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.00020316249 |
| 626 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00015471495 |
| 733 | Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption | 2010 | SIGMOD | 0.00014377067 |
| 1,991 | Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy | 2012 | VLDB | 9.2419484e-05 |
| 2,453 | Personalized Privacy Preservation | 2006 | SIGMOD | 8.439518e-05 |
| 2,855 | iReduct: Differential Privacy with Reduced Relative Errors | 2011 | SIGMOD | 7.93537e-05 |
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