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One-shot Empirical Privacy Estimation for Federated Learning

One-shot Empirical Privacy Estimation for Federated Learning

6 February 2023
Galen Andrew
Peter Kairouz
Sewoong Oh
Alina Oprea
H. B. McMahan
Vinith M. Suriyakumar
    FedML
ArXivPDFHTML

Papers citing "One-shot Empirical Privacy Estimation for Federated Learning"

8 / 8 papers shown
Title
Towards One-shot Federated Learning: Advances, Challenges, and Future Directions
Towards One-shot Federated Learning: Advances, Challenges, and Future Directions
Flora Amato
Lingyu Qiu
Mohammad Tanveer
S. Cuomo
F. Giampaolo
F. Piccialli
FedML
55
0
0
05 May 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Sangyeon Yoon
Wonje Jeung
Albert No
85
0
0
02 Dec 2024
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
Thomas Steinke
Milad Nasr
Arun Ganesh
Borja Balle
Christopher A. Choquette-Choo
Matthew Jagielski
Jamie Hayes
Abhradeep Thakurta
Adam Smith
Andreas Terzis
23
7
0
08 Oct 2024
Revealing the True Cost of Locally Differentially Private Protocols: An
  Auditing Perspective
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
Héber H. Arcolezi
Sébastien Gambs
25
1
0
04 Sep 2023
Composition of Differential Privacy & Privacy Amplification by
  Subsampling
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
54
50
0
02 Oct 2022
Bounding Training Data Reconstruction in Private (Deep) Learning
Bounding Training Data Reconstruction in Private (Deep) Learning
Chuan Guo
Brian Karrer
Kamalika Chaudhuri
L. V. D. van der Maaten
103
53
0
28 Jan 2022
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
178
154
0
26 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
1,808
0
14 Dec 2020
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