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Provable Privacy with Non-Private Pre-Processing

Provable Privacy with Non-Private Pre-Processing

19 March 2024
Yaxian Hu
Amartya Sanyal
Bernhard Schölkopf
ArXivPDFHTML

Papers citing "Provable Privacy with Non-Private Pre-Processing"

4 / 4 papers shown
Title
A Refreshment Stirred, Not Shaken (III): Can Swapping Be Differentially Private?
A Refreshment Stirred, Not Shaken (III): Can Swapping Be Differentially Private?
J. Bailie
Ruobin Gong
X. Meng
24
0
0
21 Apr 2025
Feature Selection from Differentially Private Correlations
Feature Selection from Differentially Private Correlations
Ryan Swope
Amol Khanna
Philip Doldo
Saptarshi Roy
Edward Raff
22
3
0
20 Aug 2024
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
242
593
0
14 Jul 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for
  Private Learning
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu
Huishuai Zhang
Wei Chen
Tie-Yan Liu
FedML
SILM
94
110
0
25 Feb 2021
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