Multi-Analyst Differential Privacy for Online Query Answering
Summary: Extend multi-analyst DP to online queries and show unknown query order induces a fundamental limit on queries answerable under equitable budget-sharing. Offer two solutions: a desiderata-preserving but throughput-limited mechanism, and an input-randomizing wrapper to adapt existing online DP methods. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. David Pujol
- 2. Albert Sun
- 3. Brandon Fain
- 4. Ashwin Machanavajjhala
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,416 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7309698e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 137 | Revealing Information while Preserving Privacy | 2003 | PODS | 0.00042381562 |
| 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 |
| 742 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00017336928 |
| 872 | Differentially Private Data Cubes: Optimizing Noise Sources and Consistency | 2011 | SIGMOD | 0.00015702532 |
| 2,436 | Optimizing error of high-dimensional statistical queries under differential privacy | 2018 | VLDB | 8.8217855e-05 |
| 5,249 | Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics | 2017 | SIGMOD | 5.600946e-05 |
| 7,620 | Budget Sharing for Multi-Analyst Differential Privacy | 2021 | VLDB | 4.6896122e-05 |
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