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RobustART: Benchmarking Robustness on Architecture Design and Training
  Techniques
v1v2v3v4 (latest)

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

11 September 2021
Shiyu Tang
Ruihao Gong
Yan Wang
Aishan Liu
Jiakai Wang
Xinyun Chen
F. Yu
Xianglong Liu
Basel Alomair
Alan Yuille
Philip Torr
Dacheng Tao
    VLMAAML
ArXiv (abs)PDFHTML

Papers citing "RobustART: Benchmarking Robustness on Architecture Design and Training Techniques"

44 / 94 papers shown
Title
On Evaluating Adversarial Robustness
On Evaluating Adversarial Robustness
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
Aleksander Madry
Alexey Kurakin
ELMAAML
98
905
0
18 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
149
2,559
0
24 Jan 2019
Feature Denoising for Improving Adversarial Robustness
Feature Denoising for Improving Adversarial Robustness
Cihang Xie
Yuxin Wu
Laurens van der Maaten
Alan Yuille
Kaiming He
113
912
0
09 Dec 2018
Decoupling Direction and Norm for Efficient Gradient-Based L2
  Adversarial Attacks and Defenses
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses
Jérôme Rony
L. G. Hafemann
Luiz Eduardo Soares de Oliveira
Ismail Ben Ayed
R. Sabourin
Eric Granger
AAML
63
298
0
23 Nov 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the
  Robustness of 18 Deep Image Classification Models
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D. Su
Huan Zhang
Hongge Chen
Jinfeng Yi
Pin-Yu Chen
Yupeng Gao
VLM
134
393
0
05 Aug 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture
  Design
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
Ningning Ma
Xiangyu Zhang
Haitao Zheng
Jian Sun
181
5,006
0
30 Jul 2018
Adversarial Robustness Toolbox v1.0.0
Adversarial Robustness Toolbox v1.0.0
Maria-Irina Nicolae
M. Sinn
Minh-Ngoc Tran
Beat Buesser
Ambrish Rawat
...
Nathalie Baracaldo
Bryant Chen
Heiko Ludwig
Ian Molloy
Ben Edwards
AAMLVLM
77
460
0
03 Jul 2018
Learning to Drive in a Day
Learning to Drive in a Day
Alex Kendall
Jeffrey Hawke
David Janz
Przemyslaw Mazur
Daniele Reda
John M. Allen
Vinh-Dieu Lam
Alex Bewley
Amar Shah
104
657
0
01 Jul 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Lei Ma
Felix Juefei Xu
Fuyuan Zhang
Jiyuan Sun
Minhui Xue
...
Ting Su
Li Li
Yang Liu
Jianjun Zhao
Yadong Wang
ELM
67
622
0
20 Mar 2018
Adversarial Logit Pairing
Adversarial Logit Pairing
Harini Kannan
Alexey Kurakin
Ian Goodfellow
AAML
98
628
0
16 Mar 2018
Averaging Weights Leads to Wider Optima and Better Generalization
Averaging Weights Leads to Wider Optima and Better Generalization
Pavel Izmailov
Dmitrii Podoprikhin
T. Garipov
Dmitry Vetrov
A. Wilson
FedMLMoMe
135
1,670
0
14 Mar 2018
Hessian-based Analysis of Large Batch Training and Robustness to
  Adversaries
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Z. Yao
A. Gholami
Qi Lei
Kurt Keutzer
Michael W. Mahoney
69
167
0
22 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
J. Uesato
Brendan O'Donoghue
Aaron van den Oord
Pushmeet Kohli
AAML
160
605
0
15 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
243
3,194
0
01 Feb 2018
Generalizable Data-free Objective for Crafting Universal Adversarial
  Perturbations
Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations
Konda Reddy Mopuri
Aditya Ganeshan
R. Venkatesh Babu
AAML
109
206
0
24 Jan 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
204
19,333
0
13 Jan 2018
Defense against Adversarial Attacks Using High-Level Representation
  Guided Denoiser
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser
Fangzhou Liao
Ming Liang
Yinpeng Dong
Tianyu Pang
Xiaolin Hu
Jun Zhu
83
887
0
08 Dec 2017
Progressive Neural Architecture Search
Progressive Neural Architecture Search
Chenxi Liu
Barret Zoph
Maxim Neumann
Jonathon Shlens
Wei Hua
Li Li
Li Fei-Fei
Alan Yuille
Jonathan Huang
Kevin Patrick Murphy
114
1,994
0
02 Dec 2017
On the Robustness of Semantic Segmentation Models to Adversarial Attacks
On the Robustness of Semantic Segmentation Models to Adversarial Attacks
Anurag Arnab
O. Mikšík
Philip Torr
AAML
98
307
0
27 Nov 2017
Mitigating Adversarial Effects Through Randomization
Mitigating Adversarial Effects Through Randomization
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Zhou Ren
Alan Yuille
AAML
115
1,061
0
06 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
289
9,803
0
25 Oct 2017
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
SILMOOD
315
12,131
0
19 Jun 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,862
0
14 Jun 2017
Parseval Networks: Improving Robustness to Adversarial Examples
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
AAML
145
808
0
28 Apr 2017
Genetic CNN
Genetic CNN
Lingxi Xie
Alan Yuille
3DV
129
845
0
04 Mar 2017
Regularizing Neural Networks by Penalizing Confident Output
  Distributions
Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra
George Tucker
J. Chorowski
Lukasz Kaiser
Geoffrey E. Hinton
NoLa
165
1,141
0
23 Jan 2017
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Zhuowen Tu
Kaiming He
522
10,347
0
16 Nov 2016
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
Basel Alomair
AAML
143
1,741
0
08 Nov 2016
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
148
2,533
0
26 Oct 2016
An overview of gradient descent optimization algorithms
An overview of gradient descent optimization algorithms
Sebastian Ruder
ODL
206
6,202
0
15 Sep 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
786
36,881
0
25 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
273
8,583
0
16 Aug 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
350
8,174
0
13 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
545
5,910
0
08 Jul 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
351
8,000
0
23 May 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
381
14,263
0
23 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,426
0
10 Dec 2015
Distillation as a Defense to Adversarial Perturbations against Deep
  Neural Networks
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot
Patrick McDaniel
Xi Wu
S. Jha
A. Swami
AAML
113
3,076
0
14 Nov 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
364
19,733
0
09 Mar 2015
DeepID3: Face Recognition with Very Deep Neural Networks
DeepID3: Face Recognition with Very Deep Neural Networks
Yi Sun
Ding Liang
Xiaogang Wang
Xiaoou Tang
CVBM
85
940
0
03 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,121
0
20 Dec 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLMObjD
1.7K
39,595
0
01 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
578
27,327
0
01 Sep 2014
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
282
14,963
1
21 Dec 2013
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