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On the Challenges of Deploying Privacy-Preserving Synthetic Data in the
  Enterprise

On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise

9 July 2023
L. Arthur
Jason W Costello
Jonathan Hardy
Will O'Brien
J. Rea
Gareth Rees
Georgi Ganev
ArXivPDFHTML

Papers citing "On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise"

3 / 3 papers shown
Title
Robin Hood and Matthew Effects: Differential Privacy Has Disparate
  Impact on Synthetic Data
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev
Bristena Oprisanu
Emiliano De Cristofaro
24
57
0
23 Sep 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating
  and Auditing Generative Models
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
Ahmed Alaa
B. V. Breugel
Evgeny S. Saveliev
M. Schaar
38
186
0
17 Feb 2021
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
267
1,798
0
14 Dec 2020
1