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Differentially Private Query Release Through Adaptive Projection
Sergul Aydore · William Brown · Michael Kearns · Krishnaram Kenthapadi · Luca Melis · Aaron Roth · Ankit Siva

Thu Jul 22 06:00 AM -- 06:20 AM (PDT) @

We propose, implement, and evaluate a new algo-rithm for releasing answers to very large numbersof statistical queries likek-way marginals, sub-ject to differential privacy. Our algorithm makesadaptive use of a continuous relaxation of thePro-jection Mechanism, which answers queries on theprivate dataset using simple perturbation, and thenattempts to find the synthetic dataset that mostclosely matches the noisy answers. We use a con-tinuous relaxation of the synthetic dataset domainwhich makes the projection loss differentiable,and allows us to use efficient ML optimizationtechniques and tooling. Rather than answering allqueries up front, we make judicious use of ourprivacy budget by iteratively finding queries forwhich our (relaxed) synthetic data has high error,and then repeating the projection. Randomizedrounding allows us to obtain synthetic data in theoriginal schema. We perform experimental evalu-ations across a range of parameters and datasets,and find that our method outperforms existingalgorithms on large query classes.

Author Information

Sergul Aydore (Amazon Web Services)

Sergul Aydore is an applied scientist at Amazon Web Services (AWS). Prior to AWS, Sergul was an Assistant Professor at the department of Electrical and Computer Engineering of Stevens Institute of Technology. She received her PhD degree from the Signal and Image Processing Institute at the University of Southern California in 2014. Her PhD work was on developing robust connectivity measures for neuroimaging data. She was the recipient of the Viterbi School of Engineering Doctoral Fellowship and was recognized as a 2014 USC Ming Hsieh Institute Ph.D. Scholar. Sergul has published in top-tier machine learning conferences such as ICML and NeurIPS on advancing generalization in machine learning models. She also served as an area chair in WiML at NeurIPS 2019. Her research at Stevens was supported by AWS ML Research Awards.

William Brown (Columbia University)
Michael Kearns (University of Pennsylvania)
Krishnaram Kenthapadi (Amazon AWS AI)
Luca Melis (Amazon Web Services)
Aaron Roth (University of Pennsylvania)
Ankit Siva (Amazon)

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