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Overparametrization improves robustness against adversarial attacks: A
  replication study

Overparametrization improves robustness against adversarial attacks: A replication study

20 February 2022
Ali Borji
    AAML
ArXivPDFHTML

Papers citing "Overparametrization improves robustness against adversarial attacks: A replication study"

12 / 12 papers shown
Title
The curse of overparametrization in adversarial training: Precise
  analysis of robust generalization for random features regression
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression
Hamed Hassani
Adel Javanmard
AAML
26
36
0
13 Jan 2022
A Universal Law of Robustness via Isoperimetry
A Universal Law of Robustness via Isoperimetry
Sébastien Bubeck
Mark Sellke
38
218
0
26 May 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded
  Adversarial Examples
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal
Chongli Qin
J. Uesato
Timothy A. Mann
Pushmeet Kohli
AAML
47
331
0
07 Oct 2020
A law of robustness for two-layers neural networks
A law of robustness for two-layers neural networks
Sébastien Bubeck
Yuanzhi Li
Dheeraj M. Nagaraj
62
57
0
30 Sep 2020
Deep Double Descent: Where Bigger Models and More Data Hurt
Deep Double Descent: Where Bigger Models and More Data Hurt
Preetum Nakkiran
Gal Kaplun
Yamini Bansal
Tristan Yang
Boaz Barak
Ilya Sutskever
119
940
0
04 Dec 2019
Intriguing properties of adversarial training at scale
Intriguing properties of adversarial training at scale
Cihang Xie
Alan Yuille
AAML
46
68
0
10 Jun 2019
Do ImageNet Classifiers Generalize to ImageNet?
Do ImageNet Classifiers Generalize to ImageNet?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OOD
SSeg
VLM
113
1,714
0
13 Feb 2019
Reconciling modern machine learning practice and the bias-variance
  trade-off
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
227
1,644
0
28 Dec 2018
ImageNet-trained CNNs are biased towards texture; increasing shape bias
  improves accuracy and robustness
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos
Patricia Rubisch
Claudio Michaelis
Matthias Bethge
Felix Wichmann
Wieland Brendel
100
2,666
0
29 Nov 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study
Sensitivity and Generalization in Neural Networks: an Empirical Study
Roman Novak
Yasaman Bahri
Daniel A. Abolafia
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
AAML
93
439
0
23 Feb 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
299
12,060
0
19 Jun 2017
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
269
19,045
0
20 Dec 2014
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