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Differential Privacy in the Shuffle Model: A Survey of Separations
25 July 2021
Albert Cheu
FedML
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Papers citing
"Differential Privacy in the Shuffle Model: A Survey of Separations"
8 / 8 papers shown
Title
Computationally Differentially Private Inner Product Protocols Imply Oblivious Transfer
Iftach Haitner
N. Mazor
Jad Silbak
Eliad Tsfadia
Chao Yan
86
1
0
21 Feb 2025
Analyzing the Shuffle Model through the Lens of Quantitative Information Flow
Mireya Jurado
Ramon G. Gonze
Mário S. Alvim
C. Palamidessi
66
1
0
22 May 2023
Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice
Andrea Gadotti
Frederick Sell
Reethika Ramesh
Jinyuan Jia
55
18
0
14 Apr 2023
On Privacy and Personalization in Cross-Silo Federated Learning
Ziyu Liu
Shengyuan Hu
Zhiwei Steven Wu
Virginia Smith
FedML
113
56
0
16 Jun 2022
Shuffle Private Linear Contextual Bandits
Sayak Ray Chowdhury
Xingyu Zhou
FedML
98
27
0
11 Feb 2022
Uniformity Testing in the Shuffle Model: Simpler, Better, Faster
C. Canonne
Hongyi Lyu
FedML
90
6
0
20 Aug 2021
Tight Accounting in the Shuffle Model of Differential Privacy
A. Koskela
Mikko A. Heikkilä
Antti Honkela
FedML
65
17
0
01 Jun 2021
The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model
Kobbi Nissim
Chao Yan
138
1
0
29 Mar 2021
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