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1803.01442
Cited By
Stochastic Activation Pruning for Robust Adversarial Defense
5 March 2018
Guneet Singh Dhillon
Kamyar Azizzadenesheli
Zachary Chase Lipton
Jeremy Bernstein
Jean Kossaifi
Aran Khanna
Anima Anandkumar
AAML
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Papers citing
"Stochastic Activation Pruning for Robust Adversarial Defense"
50 / 324 papers shown
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack
Hakmin Lee
Hong Joo Lee
S. T. Kim
Yong Man Ro
FedML
OOD
AAML
218
10
0
21 May 2020
Harnessing adversarial examples with a surprisingly simple defense
Ali Borji
AAML
137
0
0
26 Apr 2020
Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks
Jianhe Yuan
Zhihai He
AAML
152
27
0
23 Apr 2020
Single-step Adversarial training with Dropout Scheduling
Computer Vision and Pattern Recognition (CVPR), 2020
S. VivekB.
R. Venkatesh Babu
OOD
AAML
136
79
0
18 Apr 2020
Adversarial Weight Perturbation Helps Robust Generalization
Dongxian Wu
Shutao Xia
Yisen Wang
OOD
AAML
228
18
0
13 Apr 2020
Blind Adversarial Pruning: Balance Accuracy, Efficiency and Robustness
IEEE International Conference on Multimedia and Expo (ICME), 2020
Haidong Xie
Lixin Qian
Xueshuang Xiang
Naijin Liu
AAML
87
1
0
10 Apr 2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations
IEEE International Joint Conference on Neural Network (IJCNN), 2020
Jay Nandy
Wynne Hsu
Yang Deng
AAML
184
12
0
05 Apr 2020
Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes
Computer Vision and Pattern Recognition (CVPR), 2020
Sravanti Addepalli
S. VivekB.
Arya Baburaj
Gaurang Sriramanan
R. Venkatesh Babu
AAML
92
38
0
01 Apr 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Computer Vision and Pattern Recognition (CVPR), 2020
Tianlong Chen
Sijia Liu
Shiyu Chang
Yu Cheng
Lisa Amini
Zinan Lin
AAML
272
275
0
28 Mar 2020
Adversarial Imitation Attack
Mingyi Zhou
Jing Wu
Yipeng Liu
Xiaolin Huang
Shuaicheng Liu
Xiang Zhang
Ce Zhu
AAML
141
0
0
28 Mar 2020
DaST: Data-free Substitute Training for Adversarial Attacks
Computer Vision and Pattern Recognition (CVPR), 2020
Mingyi Zhou
Jing Wu
Yipeng Liu
Shuaicheng Liu
Ce Zhu
208
168
0
28 Mar 2020
Defense Through Diverse Directions
International Conference on Machine Learning (ICML), 2020
Christopher M. Bender
Yang Li
Yifeng Shi
Michael K. Reiter
Junier B. Oliva
AAML
150
4
0
24 Mar 2020
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations
European Conference on Computer Vision (ECCV), 2020
Saima Sharmin
Nitin Rathi
Priyadarshini Panda
Kaushik Roy
AAML
324
107
0
23 Mar 2020
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation
IEEE International Conference on Computer Vision (ICCV), 2020
Xiaohan Li
Hengshuang Zhao
Jiaya Jia
AAML
192
46
0
14 Mar 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training
Bai Li
Shiqi Wang
Yunhan Jia
Yantao Lu
Zhenyu Zhong
Lawrence Carin
Suman Jana
AAML
251
14
0
06 Mar 2020
Are L2 adversarial examples intrinsically different?
Mingxuan Li
Jingyuan Wang
Yufan Wu
AAML
135
0
0
28 Feb 2020
Randomization matters. How to defend against strong adversarial attacks
International Conference on Machine Learning (ICML), 2020
Rafael Pinot
Raphael Ettedgui
Geovani Rizk
Y. Chevaleyre
Jamal Atif
AAML
279
62
0
26 Feb 2020
HYDRA: Pruning Adversarially Robust Neural Networks
Vikash Sehwag
Shiqi Wang
Prateek Mittal
Suman Jana
AAML
219
25
0
24 Feb 2020
A Model-Based Derivative-Free Approach to Black-Box Adversarial Examples: BOBYQA
Giuseppe Ughi
V. Abrol
Jared Tanner
AAML
119
3
0
24 Feb 2020
AdvMS: A Multi-source Multi-cost Defense Against Adversarial Attacks
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Tianlin Li
Siyue Wang
Pin-Yu Chen
Xinyu Lin
Peter Chin
AAML
157
3
0
19 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses
Neural Information Processing Systems (NeurIPS), 2020
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
574
913
0
19 Feb 2020
Block Switching: A Stochastic Approach for Deep Learning Security
Tianlin Li
Siyue Wang
Pin-Yu Chen
Xinyu Lin
S. Chin
AAML
103
23
0
18 Feb 2020
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness
International Conference on Machine Learning (ICML), 2020
Aounon Kumar
Alexander Levine
Tom Goldstein
Soheil Feizi
213
102
0
08 Feb 2020
Regularizers for Single-step Adversarial Training
S. VivekB.
R. Venkatesh Babu
AAML
89
7
0
03 Feb 2020
Towards Sharper First-Order Adversary with Quantized Gradients
Zhuanghua Liu
Ivor W. Tsang
AAML
113
0
0
01 Feb 2020
Post-Training Piecewise Linear Quantization for Deep Neural Networks
European Conference on Computer Vision (ECCV), 2020
Jun Fang
Ali Shafiee
Hamzah Abdel-Aziz
D. Thorsley
Georgios Georgiadis
Joseph Hassoun
MQ
428
172
0
31 Jan 2020
Weighted Average Precision: Adversarial Example Detection in the Visual Perception of Autonomous Vehicles
Yilan Li
Senem Velipasalar
AAML
145
8
0
25 Jan 2020
GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems
Yanmao Man
Ming Li
Ryan M. Gerdes
AAML
180
8
0
21 Jan 2020
Benchmarking Adversarial Robustness
Yinpeng Dong
Qi-An Fu
Xiao Yang
Tianyu Pang
Hang Su
Zihao Xiao
Jun Zhu
AAML
183
37
0
26 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
International Conference on Learning Representations (ICLR), 2019
Jinyuan Jia
Xiaoyu Cao
Binghui Wang
Neil Zhenqiang Gong
AAML
166
104
0
20 Dec 2019
Training Provably Robust Models by Polyhedral Envelope Regularization
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
Chen Liu
Mathieu Salzmann
Sabine Süsstrunk
AAML
222
9
0
10 Dec 2019
A Survey of Black-Box Adversarial Attacks on Computer Vision Models
Siddhant Bhambri
Sumanyu Muku
Avinash Tulasi
Arun Balaji Buduru
AAML
VLM
259
89
0
03 Dec 2019
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples
Computer Vision and Pattern Recognition (CVPR), 2019
Chang Xiao
Changxi Zheng
AAML
174
21
0
25 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review
R. Wiyatno
Anqi Xu
Ousmane Amadou Dia
A. D. Berker
AAML
234
114
0
13 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks
Shai Rozenberg
G. Elidan
Ran El-Yaniv
AAML
120
1
0
03 Nov 2019
A Useful Taxonomy for Adversarial Robustness of Neural Networks
Trends in Computer Science and Information Technology (TCSIT), 2019
L. Smith
AAML
135
6
0
23 Oct 2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation
International Conference on Artificial Neural Networks (ICANN), 2019
A. Sarkar
Nikhil Kumar Gupta
Raghu Sesha Iyengar
AAML
137
11
0
17 Oct 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
Yogesh Balaji
Tom Goldstein
Judy Hoffman
AAML
327
111
0
17 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Neural Information Processing Systems (NeurIPS), 2019
Tao Yu
Shengyuan Hu
Chuan Guo
Wei-Lun Chao
Kilian Q. Weinberger
AAML
239
112
0
16 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation
Elahe Arani
F. Sarfraz
Bahram Zonooz
180
6
0
11 Oct 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks
International Conference on Cyberworlds (ICC), 2019
Rémi Bernhard
Pierre-Alain Moëllic
J. Dutertre
AAML
MQ
233
18
0
27 Sep 2019
Robust Local Features for Improving the Generalization of Adversarial Training
International Conference on Learning Representations (ICLR), 2019
Chuanbiao Song
Kun He
Jiadong Lin
Liwei Wang
John E. Hopcroft
OOD
AAML
296
76
0
23 Sep 2019
Training Robust Deep Neural Networks via Adversarial Noise Propagation
IEEE Transactions on Image Processing (TIP), 2019
Aishan Liu
Xianglong Liu
Chongzhi Zhang
Hang Yu
Qiang Liu
Dacheng Tao
AAML
129
136
0
19 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2019
Sekitoshi Kanai
Yasutoshi Ida
Yasuhiro Fujiwara
Masanori Yamada
S. Adachi
AAML
148
1
0
19 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
International Journal of Automation and Computing (IJAC), 2019
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Shucheng Zhou
Anil K. Jain
AAML
352
729
0
17 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial Configurations
Software Product Lines Conference (SPLC), 2019
Paul Temple
M. Acher
Gilles Perrouin
Battista Biggio
J. Jézéquel
Fabio Roli
AAML
88
12
0
16 Sep 2019
FDA: Feature Disruptive Attack
IEEE International Conference on Computer Vision (ICCV), 2019
Aditya Ganeshan
S. VivekB.
R. Venkatesh Babu
AAML
274
131
0
10 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
International Conference on Learning Representations (ICLR), 2019
Uyeong Jang
Susmit Jha
S. Jha
AAML
277
14
0
07 Sep 2019
Metric Learning for Adversarial Robustness
Neural Information Processing Systems (NeurIPS), 2019
Chengzhi Mao
Ziyuan Zhong
Junfeng Yang
Carl Vondrick
Baishakhi Ray
OOD
339
201
0
03 Sep 2019
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing
Frontiers in Artificial Intelligence (FAI), 2019
Dou Goodman
Xingjian Li
Ji Liu
Jun Huan
Tao Wei
AAML
112
9
0
23 Aug 2019
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