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Boosting the Accuracy of Differentially Private Histograms Through Consistency
Summary: Selects a tuned set of histogram queries and enforces consistency on the noisy DP output, then projects to the nearest consistent input. This post-processing yields higher accuracy for DP histograms, enabling precise degree-sequence estimation and accurate range queries.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 10146
- Venue
- VLDB
- Year
- 2010
- Pagerank
- 0.00037697111
- Overall Rank
- 178 | 98.77%
- DOI
-
-
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 22 of 72 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 7,997 |
Optimizing Fitness-For-Use of Differentially Private Linear Queries |
2021 |
VLDB |
4.6105691e-05 |
| 8,120 |
Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures |
2023 |
VLDB |
4.5809563e-05 |
| 8,234 |
Robust Privacy-Preserving Triangle Counting under Edge Local Differential Privacy |
2025 |
SIGMOD |
4.5535352e-05 |
| 8,418 |
Differentially Private Hierarchical Count-of-Counts Histograms |
2018 |
VLDB |
4.5183077e-05 |
| 8,837 |
Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration |
2023 |
VLDB |
4.4393184e-05 |
| 8,965 |
Universally Optimal Privacy Mechanisms for Minimax Agents |
2010 |
PODS |
4.4196402e-05 |
| 9,285 |
PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy |
2024 |
VLDB |
4.3623546e-05 |
| 9,393 |
PrivRM: A Framework for Range Mean Estimation under Local Differential Privacy |
2025 |
SIGMOD |
4.3441378e-05 |
| 9,405 |
Common Neighborhood Estimation over Bipartite Graphs under Local Differential Privacy |
2024 |
SIGMOD |
4.3441378e-05 |
| 9,512 |
Answering Private Linear Queries Adaptively using the Common Mechanism |
2023 |
VLDB |
4.3335882e-05 |
| 9,513 |
Multi-Analyst Differential Privacy for Online Query Answering |
2023 |
VLDB |
4.3335882e-05 |
| 9,514 |
Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements |
2021 |
SIGMOD |
4.3335882e-05 |
| 9,592 |
HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data |
2022 |
VLDB |
4.3202988e-05 |
| 10,015 |
Differentially Private Explanations for Clusters |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,153 |
Defense against Poisoning Attacks under Shuffle-DP |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,157 |
Efficient and Effective Biclique Counting with Local Differential Privacy |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,354 |
Private Synthetic Data Generation in Bounded Memory |
2025 |
PODS |
4.1945683e-05 |
| 10,480 |
Efficient and Accurate Differentially Private Cardinality Continual Releases |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,521 |
RM2: Answer Counting Queries Efficiently under Shuffle Differential Privacy |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,909 |
Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections |
2024 |
PODS |
4.1945683e-05 |
| 11,434 |
Data-Independent Space Partitionings for Summaries |
2021 |
PODS |
4.1945683e-05 |
| 11,879 |
Design of Policy-Aware Differentially Private Algorithms |
2016 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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