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Get Fooled for the Right Reason: Improving Adversarial Robustness
  through a Teacher-guided Curriculum Learning Approach

Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach

30 October 2021
A. Sarkar
Anirban Sarkar
Sowrya Gali
V. Balasubramanian
    AAML
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Papers citing "Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach"

4 / 4 papers shown
Title
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
36
16
0
28 Jun 2022
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
194
345
0
15 Dec 2021
Instance adaptive adversarial training: Improved accuracy tradeoffs in
  neural nets
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
Yogesh Balaji
Tom Goldstein
Judy Hoffman
AAML
131
103
0
17 Oct 2019
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
1