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Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under
  Streaming Differential Privacy

Improved Communication-Privacy Trade-offs in L2L_2L2​ Mean Estimation under Streaming Differential Privacy

2 May 2024
Wei-Ning Chen
Berivan Isik
Peter Kairouz
Albert No
Sewoong Oh
Zheng Xu
ArXivPDFHTML

Papers citing "Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy"

5 / 5 papers shown
Title
Sparse Random Networks for Communication-Efficient Federated Learning
Sparse Random Networks for Communication-Efficient Federated Learning
Berivan Isik
Francesco Pase
Deniz Gunduz
Tsachy Weissman
M. Zorzi
FedML
70
52
0
30 Sep 2022
DRIVE: One-bit Distributed Mean Estimation
DRIVE: One-bit Distributed Mean Estimation
S. Vargaftik
Ran Ben-Basat
Amit Portnoy
Gal Mendelson
Y. Ben-Itzhak
Michael Mitzenmacher
OOD
FedML
66
51
0
18 May 2021
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
178
154
0
26 Feb 2021
An Information-Theoretic Justification for Model Pruning
An Information-Theoretic Justification for Model Pruning
Berivan Isik
Tsachy Weissman
Albert No
84
35
0
16 Feb 2021
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
136
420
0
29 Nov 2018
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