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Scalable and Differentially Private Distributed Aggregation in the
  Shuffled Model

Scalable and Differentially Private Distributed Aggregation in the Shuffled Model

19 June 2019
Badih Ghazi
Rasmus Pagh
A. Velingker
    FedML
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Papers citing "Scalable and Differentially Private Distributed Aggregation in the Shuffled Model"

14 / 14 papers shown
Title
Stronger Privacy Amplification by Shuffling for Rényi and Approximate
  Differential Privacy
Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy
Vitaly Feldman
Audra McMillan
Kunal Talwar
FedML
23
47
0
09 Aug 2022
Pure Differential Privacy from Secure Intermediaries
Pure Differential Privacy from Secure Intermediaries
Albert Cheu
Chao Yan
FedML
12
9
0
19 Dec 2021
Differentially Private Federated Learning on Heterogeneous Data
Differentially Private Federated Learning on Heterogeneous Data
Maxence Noble
A. Bellet
Aymeric Dieuleveut
FedML
11
102
0
17 Nov 2021
Private Retrieval, Computing and Learning: Recent Progress and Future
  Challenges
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges
S. Ulukus
Salman Avestimehr
Michael C. Gastpar
S. Jafar
Ravi Tandon
Chao Tian
FedML
25
64
0
30 Jul 2021
A Field Guide to Federated Optimization
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
...
Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
184
411
0
14 Jul 2021
Shuffle Private Stochastic Convex Optimization
Shuffle Private Stochastic Convex Optimization
Albert Cheu
Matthew Joseph
Jieming Mao
Binghui Peng
FedML
18
25
0
17 Jun 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with
  Vanishing Communication Overhead
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Rasmus Pagh
FedML
26
48
0
08 Jun 2021
Fast-Convergent Federated Learning
Fast-Convergent Federated Learning
Hung T. Nguyen
Vikash Sehwag
Seyyedali Hosseinalipour
Christopher G. Brinton
M. Chiang
H. Vincent Poor
FedML
24
191
0
26 Jul 2020
Connecting Robust Shuffle Privacy and Pan-Privacy
Connecting Robust Shuffle Privacy and Pan-Privacy
Victor Balcer
Albert Cheu
Matthew Joseph
Jieming Mao
FedML
20
41
0
20 Apr 2020
Pure Differentially Private Summation from Anonymous Messages
Pure Differentially Private Summation from Anonymous Messages
Badih Ghazi
Noah Golowich
Ravi Kumar
Pasin Manurangsi
Rasmus Pagh
A. Velingker
FedML
23
46
0
05 Feb 2020
Separating Local & Shuffled Differential Privacy via Histograms
Separating Local & Shuffled Differential Privacy via Histograms
Victor Balcer
Albert Cheu
FedML
37
67
0
15 Nov 2019
Improved Summation from Shuffling
Improved Summation from Shuffling
Borja Balle
James Bell
Adria Gascon
Kobbi Nissim
FedML
48
22
0
24 Sep 2019
Private Aggregation from Fewer Anonymous Messages
Private Aggregation from Fewer Anonymous Messages
Badih Ghazi
Pasin Manurangsi
Rasmus Pagh
A. Velingker
FedML
42
55
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
141
420
0
29 Nov 2018
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