Feb. 13, 2024, 5:43 a.m. | Antti Koskela Rachel Redberg Yu-Xiang Wang

cs.LG updates on arXiv.org arxiv.org

Private selection mechanisms (e.g., Report Noisy Max, Sparse Vector) are fundamental primitives of differentially private (DP) data analysis with wide applications to private query release, voting, and hyperparameter tuning. Recent work (Liu and Talwar, 2019; Papernot and Steinke, 2022) has made significant progress in both generalizing private selection mechanisms and tightening their privacy analysis using modern numerical privacy accounting tools, e.g., R\'enyi DP. But R\'enyi DP is known to be lossy when $(\epsilon,\delta)$-DP is ultimately needed, and there is a …

analysis applications cs.cr cs.lg data data analysis hyperparameter max privacy profiles progress query release report vector voting work

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