Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints

15 June 2022

Papers citing "Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints"

8 / 8 papers shown

Title
Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach Bo Jiang Wanrong Zhang Donghang Lu Jian Du Sagar Sharma Qiang Yan 93 0 0 13 Dec 2024
Private Count Release: A Simple and Scalable Approach for Private Data Analytics Ryan Rogers 54 0 0 08 Mar 2024
Randomized Response with Gradual Release of Privacy Budget Mingen Pan 30 0 0 25 Jan 2024
Time-Uniform Self-Normalized Concentration for Vector-Valued Processes Justin Whitehouse Zhiwei Steven Wu Aaditya Ramdas 83 6 0 13 Oct 2023
Adaptive Principal Component Regression with Applications to Panel Data Anish Agarwal Keegan Harris Justin Whitehouse Zhiwei Steven Wu 28 5 0 03 Jul 2023
Adaptive Privacy Composition for Accuracy-first Mechanisms Ryan M. Rogers G. Samorodnitsky Zhiwei Steven Wu Aaditya Ramdas 24 2 0 24 Jun 2023
Privacy Guarantees for Personal Mobility Data in Humanitarian Response Nitin Kohli Emily L. Aiken J. Blumenstock 29 7 0 15 Jun 2023
Individual Privacy Accounting via a Renyi Filter Vitaly Feldman Tijana Zrnic 71 86 0 25 Aug 2020