Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms
Summary: Free-gap from Noisy Max: release the noisy gap to the runner-up at no extra privacy cost, boosting downstream counting accuracy by up to 50%. Sparse Vector: adaptively budget privacy, spending less on queries well above threshold to process more queries, via a careful privacy analysis. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zeyu Ding
- 2. Yuxin Wang
- 3. Danfeng Zhang
- 4. Daniel Kifer
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,512 | Answering Private Linear Queries Adaptively using the Common Mechanism | 2023 | VLDB | 4.3335882e-05 |
| 10,664 | Calibrating Noise for Group Privacy in Subsampled Mechanisms | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
| 453 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.00022741848 |
| 2,758 | Understanding the Sparse Vector Technique for Differential Privacy | 2017 | VLDB | 8.1653216e-05 |
| 4,502 | ϵktelo: A Framework for Defining Differentially-Private Computations | 2018 | SIGMOD | 6.1366984e-05 |
| 5,246 | Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics | 2017 | SIGMOD | 5.6063332e-05 |
| 7,313 | Pythia: Data Dependent Differentially Private Algorithm Selection | 2017 | SIGMOD | 4.7651627e-05 |
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