Fast Privacy Loss Accounting for Random Allocation via Multiscale FFT
1 version
MS
Moshe Shenfeld
cs.LGstat.MLcs.CRcs.ITmath.IT
On Valency
published · living versionsPreprints & journals
10 papers in the corpus · 2019–2026The Fast Mixing Mechanism for Differential Privacy
0 citations
Efficient privacy loss accounting for subsampling and random allocation
0 citations
Near-Optimal Private Linear Regression via Iterative Hessian Mixing
0 citations
Differentially Private Nonparametric Confidence Intervals Under Minimal Distributional Assumptions
0 citations
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
0 citations
How Well Can Differential Privacy Be Audited in One Run?
1 citation
Privacy amplification by random allocation
0 citations
Generalization in the Face of Adaptivity: A Bayesian Perspective
0 citations
A New Analysis of Differential Privacy's Generalization Guarantees
20 citations
A necessary and sufficient stability notion for adaptive generalization
6 citations
Profile built from the corpus for this byline.
Author records are still filling in while the Hub is in beta. If this is your page, you'll be able to claim it soon. Spot a mistake? Tell us.