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On the Effectiveness of Regularization Against Membership Inference
  Attacks

On the Effectiveness of Regularization Against Membership Inference Attacks

9 June 2020
Yigitcan Kaya
Sanghyun Hong
Tudor Dumitras
ArXivPDFHTML

Papers citing "On the Effectiveness of Regularization Against Membership Inference Attacks"

5 / 5 papers shown
Title
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Sanghyun Hong
Fan Wu
A. Gruber
Kookjin Lee
47
0
0
12 Jan 2025
Privacy-Preserving Debiasing using Data Augmentation and Machine
  Unlearning
Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning
Zhixin Pan
Emma Andrews
Laura Chang
Prabhat Mishra
MU
46
1
0
19 Apr 2024
A Blessing of Dimensionality in Membership Inference through
  Regularization
A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan
Daniel LeJeune
Blake Mason
Hamid Javadi
Richard G. Baraniuk
32
18
0
27 May 2022
Membership Inference Attacks on Machine Learning: A Survey
Membership Inference Attacks on Machine Learning: A Survey
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Philip S. Yu
Xuyun Zhang
MIACV
35
412
0
14 Mar 2021
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
310
2,896
0
15 Sep 2016
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