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Adapting Step-size: A Unified Perspective to Analyze and Improve
  Gradient-based Methods for Adversarial Attacks

Adapting Step-size: A Unified Perspective to Analyze and Improve Gradient-based Methods for Adversarial Attacks

27 January 2023
Wei Tao
Lei Bao
Long Sheng
Gao-wei Wu
Qing Tao
    AAML
ArXivPDFHTML

Papers citing "Adapting Step-size: A Unified Perspective to Analyze and Improve Gradient-based Methods for Adversarial Attacks"

3 / 3 papers shown
Title
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
203
345
0
15 Dec 2021
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,842
0
08 Jul 2016
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
298
39,217
0
01 Sep 2014
1