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2012.07828
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Robustness Threats of Differential Privacy
14 December 2020
Nurislam Tursynbek
Aleksandr Petiushko
Ivan Oseledets
AAML
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Papers citing
"Robustness Threats of Differential Privacy"
9 / 9 papers shown
The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning
Ethan Hsu
Harry Chen
Chudi Zhong
Lesia Semenova
163
0
0
26 Nov 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li
Xiaoyu Luo
Yiyi Chen
Johannes Bjerva
594
8
0
10 Mar 2025
A Curious Case of Remarkable Resilience to Gradient Attacks via Fully Convolutional and Differentiable Front End with a Skip Connection
Leonid Boytsov
Ameya Joshi
Filipe Condessa
AAML
302
0
0
26 Feb 2024
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation
Janvi Thakkar
Giulio Zizzo
S. Maffeis
AAML
187
0
0
18 Jan 2024
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
422
6
0
07 Dec 2023
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
Jiapeng Wu
Atiyeh Ashari Ghomi
David Glukhov
Jesse C. Cresswell
Franziska Boenisch
Nicolas Papernot
AAML
319
5
0
14 Jun 2023
Differentially Private Optimizers Can Learn Adversarially Robust Models
Yuan Zhang
Zhiqi Bu
381
5
0
16 Nov 2022
Training with More Confidence: Mitigating Injected and Natural Backdoors During Training
Neural Information Processing Systems (NeurIPS), 2022
Zhenting Wang
Hailun Ding
Juan Zhai
Shiqing Ma
AAML
391
58
0
13 Feb 2022
Learning to be adversarially robust and differentially private
Jamie Hayes
Borja Balle
M. P. Kumar
FedML
283
8
0
06 Jan 2022
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