Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. (arXiv:2206.07234v1 [cs.LG])

Web: http://arxiv.org/abs/2206.07234

There is a disconnect between how researchers and practitioners handle
privacy-utility tradeoffs. Researchers primarily operate from a privacy first
perspective, setting strict privacy requirements and minimizing risk subject to
these constraints. Practitioners often desire an accuracy first perspective,
possibly satisfied with the greatest privacy they can get subject to obtaining
sufficiently small error. Ligett et al. have introduced a "noise reduction"
algorithm to address the latter perspective. The authors show that by adding
correlated Laplace noise and progressively reducing it …

accuracy arxiv constraints lg noise privacy