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On the Renyi Differential Privacy of the Shuffle Model

On the Renyi Differential Privacy of the Shuffle Model

11 May 2021
Antonious M. Girgis
Deepesh Data
Suhas Diggavi
A. Suresh
Peter Kairouz
ArXivPDFHTML

Papers citing "On the Renyi Differential Privacy of the Shuffle Model"

13 / 13 papers shown
Title
Differential Privacy for Network Assortativity
Differential Privacy for Network Assortativity
Fei Ma
Jinzhi Ouyang
Xincheng Hu
40
0
0
06 May 2025
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
Tal Wagner
FedML
53
0
0
21 Feb 2025
Universally Harmonizing Differential Privacy Mechanisms for Federated
  Learning: Boosting Accuracy and Convergence
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
Shuya Feng
Meisam Mohammady
Hanbin Hong
Shenao Yan
Ashish Kundu
Binghui Wang
Yuan Hong
FedML
41
3
0
20 Jul 2024
On the Complexity of Differentially Private Best-Arm Identification with
  Fixed Confidence
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Achraf Azize
Marc Jourdan
Aymen Al Marjani
D. Basu
32
3
0
05 Sep 2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
Shaowei Wang
FedML
26
9
0
11 Apr 2023
Near Optimal Private and Robust Linear Regression
Near Optimal Private and Robust Linear Regression
Xiyang Liu
Prateek Jain
Weihao Kong
Sewoong Oh
A. Suggala
41
9
0
30 Jan 2023
Lower Bounds for Rényi Differential Privacy in a Black-Box Setting
Lower Bounds for Rényi Differential Privacy in a Black-Box Setting
T. Kutta
Önder Askin
Martin Dunsche
17
4
0
09 Dec 2022
Discrete Distribution Estimation under User-level Local Differential
  Privacy
Discrete Distribution Estimation under User-level Local Differential Privacy
Jayadev Acharya
Yuhan Liu
Ziteng Sun
27
16
0
07 Nov 2022
Differentially Private Stochastic Linear Bandits: (Almost) for Free
Differentially Private Stochastic Linear Bandits: (Almost) for Free
Osama A. Hanna
Antonious M. Girgis
Christina Fragouli
Suhas Diggavi
FedML
27
18
0
07 Jul 2022
Differentially Private Triangle and 4-Cycle Counting in the Shuffle
  Model
Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model
Jacob Imola
Takao Murakami
Kamalika Chaudhuri
19
23
0
03 May 2022
Improved Summation from Shuffling
Improved Summation from Shuffling
Borja Balle
James Bell
Adria Gascon
Kobbi Nissim
FedML
48
22
0
24 Sep 2019
Amplification by Shuffling: From Local to Central Differential Privacy
  via Anonymity
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
Ulfar Erlingsson
Vitaly Feldman
Ilya Mironov
A. Raghunathan
Kunal Talwar
Abhradeep Thakurta
144
420
0
29 Nov 2018
Prochlo: Strong Privacy for Analytics in the Crowd
Prochlo: Strong Privacy for Analytics in the Crowd
Andrea Bittau
Ulfar Erlingsson
Petros Maniatis
Ilya Mironov
A. Raghunathan
David Lie
Mitch Rudominer
Ushasree Kode
J. Tinnés
B. Seefeld
91
278
0
02 Oct 2017
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