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 |
|---|---|---|---|---|
| 7,417 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7355114e-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 |
|---|---|---|---|---|
| 136 | Revealing Information while Preserving Privacy | 2003 | PODS | 0.0004241101 |
| 178 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.00037697111 |
| 719 | Understanding Hierarchical Methods for Differentially Private Histograms | 2013 | VLDB | 0.00017626484 |
| 742 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00017360873 |
| 878 | Differentially Private Data Cubes: Optimizing Noise Sources and Consistency | 2011 | SIGMOD | 0.00015702437 |
| 2,434 | Optimizing error of high-dimensional statistical queries under differential privacy | 2018 | VLDB | 8.8278955e-05 |
| 5,246 | Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics | 2017 | SIGMOD | 5.6063332e-05 |
| 7,619 | Budget Sharing for Multi-Analyst Differential Privacy | 2021 | VLDB | 4.6941145e-05 |
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