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Evaluating Adversarial Robustness with Expected Viable Performance

Evaluating Adversarial Robustness with Expected Viable Performance

18 September 2023
Ryan McCoppin
Colin Dawson
Sean M. Kennedy
L. Blaha
    AAML
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Papers citing "Evaluating Adversarial Robustness with Expected Viable Performance"

5 / 5 papers shown
Title
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
71
121
0
21 Feb 2022
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng
Chenhui Deng
Zhiqiang Zhao
Yaohui Cai
Zhiru Zhang
Zhuo Feng
AAML
39
13
0
07 Feb 2021
On Evaluating Adversarial Robustness
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELM
AAML
72
899
0
18 Feb 2019
Evaluating the Robustness of Neural Networks: An Extreme Value Theory
  Approach
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng
Huan Zhang
Pin-Yu Chen
Jinfeng Yi
D. Su
Yupeng Gao
Cho-Jui Hsieh
Luca Daniel
AAML
73
466
0
31 Jan 2018
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
211
14,831
1
21 Dec 2013
1