Or Sheffet
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| title | conference | date |
|---|---|---|
| Bandit Learning under Differential Privacy | Privacy and the Science of Data Analysis 2019 | 2019-04-08 |
Defines event-level pure differential privacy for bandit pulls, proves a lower bound that private algorithms must pull any suboptimal arm roughly Omega(log T… | ||
| When Existing Techniques in Linear Regression Preserve Differential Privacy | Learning, Algorithm Design and Beyond Worst-Case Analysis | 2016-11-14 |
Shows that standard regressors already give differential privacy if applied to the second-moment matrix with the right randomness and scale. Releasing the… | ||
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