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Can overfitted deep neural networks in adversarial training generalize?
  -- An approximation viewpoint

Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint

24 January 2024
Zhongjie Shi
Fanghui Liu
Yuan Cao
Johan A. K. Suykens
ArXivPDFHTML

Papers citing "Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint"

11 / 11 papers shown
Title
Exploring Memorization in Adversarial Training
Exploring Memorization in Adversarial Training
Yinpeng Dong
Ke Xu
Xiao Yang
Tianyu Pang
Zhijie Deng
Hang Su
Jun Zhu
TDI
33
72
0
03 Jun 2021
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture
  Model
Robust Classification Under ℓ0\ell_0ℓ0​ Attack for the Gaussian Mixture Model
Payam Delgosha
Hamed Hassani
Ramtin Pedarsani
AAML
35
8
0
05 Apr 2021
Overfitting in adversarially robust deep learning
Overfitting in adversarially robust deep learning
Leslie Rice
Eric Wong
Zico Kolter
62
794
0
26 Feb 2020
Lower Bounds on Adversarial Robustness from Optimal Transport
Lower Bounds on Adversarial Robustness from Optimal Transport
A. Bhagoji
Daniel Cullina
Prateek Mittal
OOD
OT
AAML
36
92
0
26 Sep 2019
Adversarial Training Can Hurt Generalization
Adversarial Training Can Hurt Generalization
Aditi Raghunathan
Sang Michael Xie
Fanny Yang
John C. Duchi
Percy Liang
42
241
0
14 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
68
1,825
0
06 May 2019
Error bounds for approximations with deep ReLU neural networks in
  $W^{s,p}$ norms
Error bounds for approximations with deep ReLU neural networks in Ws,pW^{s,p}Ws,p norms
Ingo Gühring
Gitta Kutyniok
P. Petersen
51
200
0
21 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
137
1,628
0
28 Dec 2018
Countering Adversarial Images using Input Transformations
Countering Adversarial Images using Input Transformations
Chuan Guo
Mayank Rana
Moustapha Cissé
Laurens van der Maaten
AAML
71
1,399
0
31 Oct 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
  Methods
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini
D. Wagner
AAML
86
1,851
0
20 May 2017
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
79
14,831
1
21 Dec 2013
1