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Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
v1v2v3v4 (latest)

Privacy Amplification via Shuffling: Unified, Simplified, and Tightened

11 April 2023
Shaowei Wang
    FedML
ArXiv (abs)PDFHTMLGithub (11★)

Papers citing "Privacy Amplification via Shuffling: Unified, Simplified, and Tightened"

3 / 3 papers shown
Title
Segmented Private Data Aggregation in the Multi-message Shuffle Model
Segmented Private Data Aggregation in the Multi-message Shuffle Model
Shaowei Wang
Hongqiao Chen
Sufen Zeng
Ruilin Yang
Hui Jiang
...
Kaiqi Yu
Rundong Mei
Shaozheng Huang
Wei Yang
Bangzhou Xin
FedML
128
0
0
31 Dec 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Shaowei Wang
Changyu Dong
Xiangfu Song
Jin Li
Zhili Zhou
Di Wang
Han Wu
114
0
0
26 Jun 2024
Individual Privacy Accounting for Differentially Private Stochastic
  Gradient Descent
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
Da Yu
Gautam Kamath
Janardhan Kulkarni
Tie-Yan Liu
Jian Yin
Huishuai Zhang
158
22
0
06 Jun 2022
1