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Combating Adversarial Attacks Using Sparse Representations
v1v2v3 (latest)

Combating Adversarial Attacks Using Sparse Representations

11 March 2018
S. Gopalakrishnan
Zhinus Marzi
Upamanyu Madhow
Ramtin Pedarsani
    AAML
ArXiv (abs)PDFHTML

Papers citing "Combating Adversarial Attacks Using Sparse Representations"

8 / 8 papers shown
Title
Surprises in adversarially-trained linear regression
Surprises in adversarially-trained linear regression
Antônio H. Ribeiro
Dave Zachariah
Thomas B. Schon
AAML
182
2
0
25 May 2022
On Trace of PGD-Like Adversarial Attacks
On Trace of PGD-Like Adversarial Attacks
Mo Zhou
Vishal M. Patel
AAML
75
4
0
19 May 2022
Polarizing Front Ends for Robust CNNs
Polarizing Front Ends for Robust CNNs
Can Bakiskan
S. Gopalakrishnan
Metehan Cekic
Upamanyu Madhow
Ramtin Pedarsani
AAML
37
4
0
22 Feb 2020
Minimum Uncertainty Based Detection of Adversaries in Deep Neural
  Networks
Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks
Fatemeh Sheikholeslami
Swayambhoo Jain
G. Giannakis
AAML
67
25
0
05 Apr 2019
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural
  Networks
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks
P. Langenberg
E. Balda
Arash Behboodi
R. Mathar
53
16
0
29 Jan 2019
Sparse DNNs with Improved Adversarial Robustness
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo
Chao Zhang
Changshui Zhang
Yurong Chen
AAML
100
154
0
23 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon
Adversarial Examples - A Complete Characterisation of the Phenomenon
A. Serban
E. Poll
Joost Visser
SILMAAML
102
49
0
02 Oct 2018
Motivating the Rules of the Game for Adversarial Example Research
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer
Ryan P. Adams
Ian Goodfellow
David G. Andersen
George E. Dahl
AAML
107
229
0
18 Jul 2018
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