Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets
Summary: presents wPINQ, a differential-privacy platform that improves accuracy by non-uniformly scaling weights of records instead of increasing noise. extends PINQ with a non-uniform join operator and a random-walk probabilistic inference engine to support graph analytics and synthetic-data generation with formal privacy guarantees. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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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 |
|---|---|---|---|---|
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
| 505 | Relationship Privacy: Output Perturbation for Queries with Joins | 2009 | PODS | 0.00021491332 |
| 642 | Private Analysis of Graph Structure | 2011 | VLDB | 0.00018755196 |
| 742 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00017360873 |
| 1,177 | Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins | 2013 | SIGMOD | 0.00013470212 |
| 1,681 | GUPT: Privacy Preserving Data Analysis Made Easy | 2012 | SIGMOD | 0.00010929746 |
| 2,274 | An Adaptive Mechanism for Accurate Query Answering under Differential Privacy | 2012 | VLDB | 9.1297703e-05 |
| 6,185 | Privacy-Aware Data Management in Information Networks | 2011 | SIGMOD | 5.1666285e-05 |
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