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Evaluating a Simple Retraining Strategy as a Defense Against Adversarial
  Attacks

Evaluating a Simple Retraining Strategy as a Defense Against Adversarial Attacks

20 July 2020
Nupur Thakur
Yuzhen Ding
Baoxin Li
    AAML
ArXiv (abs)PDFHTML

Papers citing "Evaluating a Simple Retraining Strategy as a Defense Against Adversarial Attacks"

5 / 5 papers shown
Title
Generative Adversarial Perturbations
Generative Adversarial Perturbations
Omid Poursaeed
Isay Katsman
Bicheng Gao
Serge J. Belongie
AAMLGANWIGM
74
355
0
06 Dec 2017
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
282
8,583
0
16 Aug 2016
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
154
4,905
0
14 Nov 2015
Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
171
3,274
0
05 Dec 2014
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
282
14,963
1
21 Dec 2013
1