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Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve
  Adversarial Robustness

Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness

2 March 2020
Ahmadreza Jeddi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
    OOD
    AAML
ArXivPDFHTML

Papers citing "Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness"

7 / 7 papers shown
Title
A Cognitive Framework for Delegation Between Error-Prone AI and Human
  Agents
A Cognitive Framework for Delegation Between Error-Prone AI and Human Agents
Andrew Fuchs
A. Passarella
M. Conti
8
7
0
06 Apr 2022
Simple Post-Training Robustness Using Test Time Augmentations and Random
  Forest
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest
Gilad Cohen
Raja Giryes
AAML
19
4
0
16 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Saeed Mian
Navid Kardan
M. Shah
AAML
20
234
0
01 Aug 2021
Disentangling Adversarial Robustness and Generalization
Disentangling Adversarial Robustness and Generalization
David Stutz
Matthias Hein
Bernt Schiele
AAML
OOD
178
271
0
03 Dec 2018
Generating Natural Language Adversarial Examples
Generating Natural Language Adversarial Examples
M. Alzantot
Yash Sharma
Ahmed Elgohary
Bo-Jhang Ho
Mani B. Srivastava
Kai-Wei Chang
AAML
233
909
0
21 Apr 2018
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
253
3,102
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,813
0
08 Jul 2016
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