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On Avoiding the Union Bound When Answering Multiple Differentially
  Private Queries

On Avoiding the Union Bound When Answering Multiple Differentially Private Queries

16 December 2020
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
    FedML
ArXivPDFHTML

Papers citing "On Avoiding the Union Bound When Answering Multiple Differentially Private Queries"

4 / 4 papers shown
Title
Sample-Optimal Locally Private Hypothesis Selection and the Provable
  Benefits of Interactivity
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity
A. F. Pour
Hassan Ashtiani
S. Asoodeh
41
0
0
09 Dec 2023
Certified private data release for sparse Lipschitz functions
Certified private data release for sparse Lipschitz functions
Konstantin Donhauser
J. Lokna
Amartya Sanyal
M. Boedihardjo
R. Honig
Fanny Yang
46
3
0
19 Feb 2023
A bounded-noise mechanism for differential privacy
A bounded-noise mechanism for differential privacy
Y. Dagan
Gil Kur
23
22
0
07 Dec 2020
Privately Learning High-Dimensional Distributions
Privately Learning High-Dimensional Distributions
Gautam Kamath
Jerry Li
Vikrant Singhal
Jonathan R. Ullman
FedML
69
148
0
01 May 2018
1