Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient

28 May 2023

Papers citing "Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient"

5 / 5 papers shown

Title
$Infinitely Divisible Noise for Differential Privacy: Nearly Optimal Error in the High $\varepsilon$ Regime$ Infinitely Divisible Noise for Differential Privacy: Nearly Optimal Error in the High $\varepsilon$ Regime Charlie Harrison Pasin Manurangsi 24 0 0 07 Apr 2025
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities Tal Wagner FedML 48 0 0 21 Feb 2025
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 55 36 0 27 Sep 2021
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 37 55 0 24 Sep 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 136 420 0 29 Nov 2018