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Denoised Smoothing: A Provable Defense for Pretrained Classifiers

Denoised Smoothing: A Provable Defense for Pretrained Classifiers

4 March 2020
Hadi Salman
Mingjie Sun
Greg Yang
Ashish Kapoor
J. Zico Kolter
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Papers citing "Denoised Smoothing: A Provable Defense for Pretrained Classifiers"

5 / 5 papers shown
Title
On the Certified Robustness for Ensemble Models and Beyond
On the Certified Robustness for Ensemble Models and Beyond
Zhuolin Yang
Linyi Li
Xiaojun Xu
B. Kailkhura
Tao Xie
Bo-wen Li
AAML
29
48
0
22 Jul 2021
Data-Dependent Randomized Smoothing
Data-Dependent Randomized Smoothing
Motasem Alfarra
Adel Bibi
Philip Torr
Guohao Li
UQCV
28
34
0
08 Dec 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against
  Adversarial Perturbations
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations
Jinyuan Jia
Binghui Wang
Xiaoyu Cao
Hongbin Liu
Neil Zhenqiang Gong
13
24
0
15 Nov 2020
Certifying Joint Adversarial Robustness for Model Ensembles
Certifying Joint Adversarial Robustness for Model Ensembles
M. Jonas
David Evans
AAML
21
2
0
21 Apr 2020
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
296
3,112
0
04 Nov 2016
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