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Lossless Compression of Efficient Private Local Randomizers

Lossless Compression of Efficient Private Local Randomizers

24 February 2021
Vitaly Feldman
Kunal Talwar
ArXivPDFHTML

Papers citing "Lossless Compression of Efficient Private Local Randomizers"

15 / 15 papers shown
Title
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Shaowei Wang
Changyu Dong
Xiangfu Song
Jin Li
Zhili Zhou
Di Wang
Han Wu
41
0
0
26 Jun 2024
Universal Exact Compression of Differentially Private Mechanisms
Universal Exact Compression of Differentially Private Mechanisms
Yanxiao Liu
Wei-Ning Chen
Ayfer Özgür
Cheuk Ting Li
42
2
0
28 May 2024
Samplable Anonymous Aggregation for Private Federated Data Analysis
Samplable Anonymous Aggregation for Private Federated Data Analysis
Kunal Talwar
Shan Wang
Audra McMillan
Vojta Jina
Vitaly Feldman
...
Congzheng Song
Karl Tarbe
Sebastian Vogt
L. Winstrom
Shundong Zhou
FedML
38
13
0
27 Jul 2023
Differentially Private Heavy Hitter Detection using Federated Analytics
Differentially Private Heavy Hitter Detection using Federated Analytics
Karan N. Chadha
Junye Chen
John C. Duchi
Vitaly Feldman
H. Hashemi
O. Javidbakht
Audra McMillan
Kunal Talwar
FedML
27
7
0
21 Jul 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in
  Distributed Mean Estimation
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation
Berivan Isik
Wei-Ning Chen
Ayfer Özgür
Tsachy Weissman
Albert No
61
19
0
08 Jun 2023
Breaking the Communication-Privacy-Accuracy Tradeoff with
  $f$-Differential Privacy
Breaking the Communication-Privacy-Accuracy Tradeoff with fff-Differential Privacy
Richeng Jin
Z. Su
C. Zhong
Zhaoyang Zhang
Tony Q.S. Quek
H. Dai
FedML
29
2
0
19 Feb 2023
Private Federated Statistics in an Interactive Setting
Private Federated Statistics in an Interactive Setting
Audra McMillan
O. Javidbakht
Kunal Talwar
Elliot Briggs
Mike Chatzidakis
...
Paul J. Pelzl
Rehan Rishi
Congzheng Song
Shan Wang
Shundong Zhou
FedML
27
6
0
18 Nov 2022
Privacy-Aware Compression for Federated Learning Through Numerical
  Mechanism Design
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design
Chuan Guo
Kamalika Chaudhuri
Pierre Stock
Michael G. Rabbat
FedML
33
7
0
08 Nov 2022
Contraction of Locally Differentially Private Mechanisms
Contraction of Locally Differentially Private Mechanisms
S. Asoodeh
Huanyu Zhang
26
10
0
24 Oct 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy
Optimal Algorithms for Mean Estimation under Local Differential Privacy
Hilal Asi
Vitaly Feldman
Kunal Talwar
40
41
0
05 May 2022
Optimal Compression of Locally Differentially Private Mechanisms
Optimal Compression of Locally Differentially Private Mechanisms
Abhin Shah
Wei-Ning Chen
Johannes Ballé
Peter Kairouz
Lucas Theis
35
42
0
29 Oct 2021
Differentially Private Histograms in the Shuffle Model from Fake Users
Differentially Private Histograms in the Shuffle Model from Fake Users
Albert Cheu
M. Zhilyaev
FedML
40
27
0
06 Apr 2021
Breaking the Communication-Privacy-Accuracy Trilemma
Breaking the Communication-Privacy-Accuracy Trilemma
Wei-Ning Chen
Peter Kairouz
Ayfer Özgür
14
116
0
22 Jul 2020
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
150
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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