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Improved robustness to adversarial examples using Lipschitz regularization of the loss

1 October 2018
Chris Finlay
Adam M. Oberman
B. Abbasi
ArXivPDFHTML

Papers citing "Improved robustness to adversarial examples using Lipschitz regularization of the loss"

6 / 6 papers shown
Title
A Learning Paradigm for Interpretable Gradients
A Learning Paradigm for Interpretable Gradients
Felipe Figueroa
Hanwei Zhang
R. Sicre
Yannis Avrithis
Stéphane Ayache
FAtt
20
0
0
23 Apr 2024
The Geometry of Adversarial Training in Binary Classification
The Geometry of Adversarial Training in Binary Classification
Leon Bungert
Nicolas García Trillos
Ryan W. Murray
AAML
24
22
0
26 Nov 2021
Coarse-Grained Smoothness for RL in Metric Spaces
Coarse-Grained Smoothness for RL in Metric Spaces
Giorgio Giannone
Kavosh Asadi
Cameron Allen
Sam Lobel
George Konidaris
Michael Littman
37
3
0
23 Oct 2021
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder
Guanlin Li
Shuya Ding
Jun Luo
Chang-rui Liu
AAML
42
19
0
06 May 2020
Interpreting Adversarial Examples by Activation Promotion and
  Suppression
Interpreting Adversarial Examples by Activation Promotion and Suppression
Kaidi Xu
Sijia Liu
Gaoyuan Zhang
Mengshu Sun
Pu Zhao
Quanfu Fan
Chuang Gan
X. Lin
AAML
FAtt
18
43
0
03 Apr 2019
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
1