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2010.01279
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Do Wider Neural Networks Really Help Adversarial Robustness?
Neural Information Processing Systems (NeurIPS), 2020
3 October 2020
Boxi Wu
Jinghui Chen
Deng Cai
Xiaofei He
Quanquan Gu
AAML
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Papers citing
"Do Wider Neural Networks Really Help Adversarial Robustness?"
27 / 77 papers shown
ADBench: Anomaly Detection Benchmark
Neural Information Processing Systems (NeurIPS), 2022
Songqiao Han
Xiyang Hu
Hailiang Huang
Mingqi Jiang
Yue Zhao
OOD
348
379
0
19 Jun 2022
Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations
Kaustubh Sridhar
Souradeep Dutta
Ramneet Kaur
James Weimer
O. Sokolsky
Insup Lee
AAML
147
4
0
13 Jun 2022
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint
International Conference on Machine Learning (ICML), 2022
Hao Liu
Minshuo Chen
Siawpeng Er
Wenjing Liao
Tong Zhang
Tuo Zhao
179
15
0
09 Jun 2022
Wavelet Regularization Benefits Adversarial Training
Jun Yan
Huilin Yin
Xiaoyang Deng
Zi-qin Zhao
Wancheng Ge
Hao Zhang
Gerhard Rigoll
AAML
195
3
0
08 Jun 2022
The robust way to stack and bag: the local Lipschitz way
Thulasi Tholeti
Sheetal Kalyani
AAML
174
5
0
01 Jun 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling
IEEE Signal Processing Magazine (IEEE Signal Process. Mag.), 2022
Lei Cheng
Feng Yin
Sergios Theodoridis
S. Chatzis
Tsung-Hui Chang
296
90
0
28 May 2022
Squeeze Training for Adversarial Robustness
International Conference on Learning Representations (ICLR), 2022
Qizhang Li
Yiwen Guo
W. Zuo
Hao Chen
OOD
244
18
0
23 May 2022
Generalizing Adversarial Explanations with Grad-CAM
Tanmay Chakraborty
Utkarsh Trehan
Khawla Mallat
J. Dugelay
FAtt
GAN
169
20
0
11 Apr 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Elvis Dohmatob
A. Bietti
AAML
364
15
0
22 Mar 2022
Understanding Adversarial Robustness from Feature Maps of Convolutional Layers
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Cong Xu
Wei Zhang
Jun Wang
Min Yang
AAML
158
2
0
25 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
International Conference on Machine Learning (ICML), 2022
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
411
150
0
21 Feb 2022
Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations
International Conference on Learning Representations (ICLR), 2022
Weiqi Peng
Jinghui Chen
AAML
131
5
0
03 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Jinghui Chen
Yuan Cao
Quanquan Gu
AAML
SILM
207
11
0
31 Dec 2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness
Konstantinos P. Panousis
S. Chatzis
Sergios Theodoridis
BDL
AAML
177
16
0
05 Dec 2021
Improving Robustness using Generated Data
Sven Gowal
Sylvestre-Alvise Rebuffi
Olivia Wiles
Florian Stimberg
D. A. Calian
Timothy A. Mann
367
351
0
18 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Neural Information Processing Systems (NeurIPS), 2021
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Jiabo He
AAML
TPM
319
112
0
07 Oct 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
Hangzhi Guo
T. Nguyen
A. Yadav
OffRL
187
21
0
15 Sep 2021
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better
Bojia Zi
Shihao Zhao
Jiabo He
Yu-Gang Jiang
AAML
181
122
0
18 Aug 2021
Interpolation can hurt robust generalization even when there is no noise
Neural Information Processing Systems (NeurIPS), 2021
Konstantin Donhauser
Alexandru cTifrea
Michael Aerni
Reinhard Heckel
Fanny Yang
255
15
0
05 Aug 2021
Learning distinct features helps, provably
Firas Laakom
Jenni Raitoharju
Alexandros Iosifidis
Moncef Gabbouj
MLT
255
6
0
10 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels
Jingfeng Zhang
Xilie Xu
Bo Han
Tongliang Liu
Gang Niu
Li-zhen Cui
Masashi Sugiyama
NoLa
AAML
196
9
0
31 May 2021
Adversarial Robustness against Multiple and Single
l
p
l_p
l
p
-Threat Models via Quick Fine-Tuning of Robust Classifiers
International Conference on Machine Learning (ICML), 2021
Francesco Croce
Matthias Hein
OOD
AAML
218
26
0
26 May 2021
Towards Robust Vision Transformer
Computer Vision and Pattern Recognition (CVPR), 2021
Xiaofeng Mao
Gege Qi
YueFeng Chen
Xiaodan Li
Ranjie Duan
Shaokai Ye
Yuan He
Hui Xue
ViT
430
228
0
17 May 2021
Boosting Adversarial Transferability through Enhanced Momentum
British Machine Vision Conference (BMVC), 2021
Xiaosen Wang
Jiadong Lin
Han Hu
Jingdong Wang
Kun He
AAML
201
95
0
19 Mar 2021
Mind the box:
l
1
l_1
l
1
-APGD for sparse adversarial attacks on image classifiers
International Conference on Machine Learning (ICML), 2021
Francesco Croce
Matthias Hein
AAML
324
65
0
01 Mar 2021
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
747
818
0
19 Oct 2020
Efficient Robust Training via Backward Smoothing
AAAI Conference on Artificial Intelligence (AAAI), 2020
Jinghui Chen
Yu Cheng
Zhe Gan
Quanquan Gu
Jingjing Liu
AAML
192
44
0
03 Oct 2020
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