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Covariance's Loss is Privacy's Gain: Computationally Efficient, Private
  and Accurate Synthetic Data

Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data

13 July 2021
M. Boedihardjo
Thomas Strohmer
Roman Vershynin
ArXivPDFHTML

Papers citing "Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data"

2 / 2 papers shown
Title
Synthetic Data -- what, why and how?
Synthetic Data -- what, why and how?
James Jordon
Lukasz Szpruch
F. Houssiau
M. Bottarelli
Giovanni Cherubin
Carsten Maple
Samuel N. Cohen
Adrian Weller
32
109
0
06 May 2022
Leveraging Public Data for Practical Private Query Release
Leveraging Public Data for Practical Private Query Release
Terrance Liu
G. Vietri
Thomas Steinke
Jonathan R. Ullman
Zhiwei Steven Wu
148
58
0
17 Feb 2021
1