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SoK: Differential Privacies

SoK: Differential Privacies

4 June 2019
Damien Desfontaines
Balázs Pejó
ArXivPDFHTML

Papers citing "SoK: Differential Privacies"

20 / 20 papers shown
Title
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy
Nicolas Küchler
Alexander Viand
Hidde Lycklama
Anwar Hithnawi
16
0
0
10 May 2025
Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data
Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data
Chih-Cheng Rex Yuan
Bow-Yaw Wang
40
0
0
30 Apr 2025
ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical
  Adversaries
ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical Adversaries
Rachel Cummings
Shlomi Hod
Jayshree Sarathy
Marika Swanberg
23
2
0
02 May 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Xinyu Tang
Ashwinee Panda
Milad Nasr
Saeed Mahloujifar
Prateek Mittal
44
18
0
09 Jan 2024
An In-Depth Examination of Requirements for Disclosure Risk Assessment
An In-Depth Examination of Requirements for Disclosure Risk Assessment
Ron S. Jarmin
John M. Abowd
Robert Ashmead
Ryan Cumings-Menon
N. Goldschlag
...
Jerome P. Reiter
Rolando A. Rodríguez
Ian M. Schmutte
V. Velkoff
Pavel I Zhuravlev
11
8
0
13 Oct 2023
Algorithms with More Granular Differential Privacy Guarantees
Algorithms with More Granular Differential Privacy Guarantees
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Thomas Steinke
42
6
0
08 Sep 2022
Bayesian and Frequentist Semantics for Common Variations of Differential
  Privacy: Applications to the 2020 Census
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census
Daniel Kifer
John M. Abowd
Robert Ashmead
Ryan Cumings-Menon
Philip Leclerc
Ashwin Machanavajjhala
William Sexton
Pavel I Zhuravlev
23
26
0
07 Sep 2022
DP-Rewrite: Towards Reproducibility and Transparency in Differentially
  Private Text Rewriting
DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting
Timour Igamberdiev
Thomas Arnold
Ivan Habernal
14
19
0
22 Aug 2022
Differential Privacy in Natural Language Processing: The Story So Far
Differential Privacy in Natural Language Processing: The Story So Far
Oleksandra Klymenko
Stephen Meisenbacher
Florian Matthes
21
15
0
17 Aug 2022
Partial sensitivity analysis in differential privacy
Partial sensitivity analysis in differential privacy
Tamara T. Mueller
Alexander Ziller
Dmitrii Usynin
Moritz Knolle
F. Jungmann
Daniel Rueckert
Georgios Kaissis
29
1
0
22 Sep 2021
The Effect of False Positives: Why Fuzzy Message Detection Leads to
  Fuzzy Privacy Guarantees?
The Effect of False Positives: Why Fuzzy Message Detection Leads to Fuzzy Privacy Guarantees?
István András Seres
Balázs Pejó
P. Burcsi
8
16
0
14 Sep 2021
Asymmetric Differential Privacy
Asymmetric Differential Privacy
Shun Takagi
Yang Cao
Masatoshi Yoshikawa
20
6
0
01 Mar 2021
Privacy-Preserving Graph Convolutional Networks for Text Classification
Privacy-Preserving Graph Convolutional Networks for Text Classification
Timour Igamberdiev
Ivan Habernal
GNN
20
33
0
10 Feb 2021
Quality Inference in Federated Learning with Secure Aggregation
Quality Inference in Federated Learning with Secure Aggregation
Balázs Pejó
G. Biczók
FedML
8
21
0
13 Jul 2020
Differential Privacy at Risk: Bridging Randomness and Privacy Budget
Differential Privacy at Risk: Bridging Randomness and Privacy Budget
Ashish Dandekar
D. Basu
S. Bressan
11
8
0
02 Mar 2020
Differentially Private SQL with Bounded User Contribution
Differentially Private SQL with Bounded User Contribution
Royce J. Wilson
Celia Yuxin Zhang
William K. C. Lam
Damien Desfontaines
Daniel Simmons-Marengo
Bryant Gipson
17
147
0
04 Sep 2019
Local Distribution Obfuscation via Probability Coupling
Local Distribution Obfuscation via Probability Coupling
Yusuke Kawamoto
Takao Murakami
17
7
0
13 Jul 2019
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
79
278
0
02 Oct 2017
Privacy Against Statistical Inference
Privacy Against Statistical Inference
Flavio du Pin Calmon
N. Fawaz
FedML
83
345
0
08 Oct 2012
Mechanism Design in Large Games: Incentives and Privacy
Michael Kearns
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
77
181
0
17 Jul 2012
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