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1905.02175
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Adversarial Examples Are Not Bugs, They Are Features
Neural Information Processing Systems (NeurIPS), 2019
6 May 2019
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
Re-assign community
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Papers citing
"Adversarial Examples Are Not Bugs, They Are Features"
50 / 1,093 papers shown
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Conference on Robot Learning (CoRL), 2021
James Tu
Huichen Li
Xinchen Yan
Mengye Ren
Yun Chen
Ming Liang
E. Bitar
Ersin Yumer
R. Urtasun
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300
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17 Jan 2021
Removing Undesirable Feature Contributions Using Out-of-Distribution Data
International Conference on Learning Representations (ICLR), 2021
Saehyung Lee
Changhwa Park
Hyungyu Lee
Jihun Yi
Jonghyun Lee
Sungroh Yoon
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323
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17 Jan 2021
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Hadjer Benkraouda
Yue Liu
Yibo Jacky Zhang
B. Kailkhura
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15 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable
International Conference on Learning Representations (ICLR), 2021
Hanxun Huang
Jiabo He
S. Erfani
James Bailey
Yisen Wang
MIACV
540
236
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13 Jan 2021
Adversarial Sample Enhanced Domain Adaptation: A Case Study on Predictive Modeling with Electronic Health Records
Yiqin Yu
Pin-Yu Chen
Yuan Zhou
Jing Mei
OOD
95
1
0
13 Jan 2021
With False Friends Like These, Who Can Notice Mistakes?
AAAI Conference on Artificial Intelligence (AAAI), 2020
Lue Tao
Lei Feng
Jinfeng Yi
Songcan Chen
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373
6
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29 Dec 2020
Byzantine-Resilient Non-Convex Stochastic Gradient Descent
International Conference on Learning Representations (ICLR), 2020
Zeyuan Allen-Zhu
Faeze Ebrahimian
Haibin Zhang
Dan Alistarh
FedML
244
87
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28 Dec 2020
Analysis of Dominant Classes in Universal Adversarial Perturbations
Knowledge-Based Systems (KBS), 2020
Jon Vadillo
Roberto Santana
Jose A. Lozano
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224
9
0
28 Dec 2020
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161
7
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28 Dec 2020
A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning
Ahmadreza Jeddi
M. Shafiee
A. Wong
AAML
208
46
0
25 Dec 2020
Unadversarial Examples: Designing Objects for Robust Vision
Neural Information Processing Systems (NeurIPS), 2020
Hadi Salman
Andrew Ilyas
Logan Engstrom
Sai H. Vemprala
Aleksander Madry
Ashish Kapoor
WIGM
215
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22 Dec 2020
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification
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Shuyang Cheng
Yingqi Liu
Shiqing Ma
Xinming Zhang
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327
179
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21 Dec 2020
On Success and Simplicity: A Second Look at Transferable Targeted Attacks
Neural Information Processing Systems (NeurIPS), 2020
Subrat Kishore Dutta
Zhuoran Liu
Martha Larson
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689
147
0
21 Dec 2020
Efficient Training of Robust Decision Trees Against Adversarial Examples
International Conference on Machine Learning (ICML), 2020
D. Vos
S. Verwer
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182
44
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18 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers
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157
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18 Dec 2020
Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience -- an initial exploration
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Daniel C. Elton
266
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Proceedings on Privacy Enhancing Technologies (PoPETs), 2020
Ivan Evtimov
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FedML
186
26
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15 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher
Journal of Computational Mathematics (JCM), 2020
Chao Ma
Lexing Ying
163
1
0
14 Dec 2020
Learning Energy-Based Models With Adversarial Training
European Conference on Computer Vision (ECCV), 2020
Xuwang Yin
Shiying Li
Gustavo K. Rohde
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DiffM
413
11
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11 Dec 2020
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis
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Neil Fendley
Philippe Burlina
AAML
323
8
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11 Dec 2020
An Empirical Review of Adversarial Defenses
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56
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10 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
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Ang Li
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Huanrui Yang
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Yiran Chen
FedML
274
199
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08 Dec 2020
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Piotr A. Sokól
SueYeon Chung
K. Harris
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OOD
142
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Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy
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OOD
86
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Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
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273
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07 Dec 2020
Are DNNs fooled by extremely unrecognizable images?
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Hiroshi Kera
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267
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A Singular Value Perspective on Model Robustness
Malhar Jere
Maghav Kumar
F. Koushanfar
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228
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07 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection
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Jihun Hamm
Sung Ju Hwang
Sooel Son
I. Shin
AAML
OOD
219
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07 Dec 2020
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations
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Xingyu Zhao
Wei Huang
Xiaowei Huang
Valentin Robu
David Flynn
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162
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Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training
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Ultrasound Diagnosis of COVID-19: Robustness and Explainability
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115
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Truly shift-invariant convolutional neural networks
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Ivan Dokmanić
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Nature Communications (Nat Commun), 2020
T. Han
S. Nebelung
F. Pedersoli
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M. Schulze-Hagen
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Fabian Kiessling
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130
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Adversarial Classification: Necessary conditions and geometric flows
Journal of machine learning research (JMLR), 2020
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305
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Spatially Correlated Patterns in Adversarial Images
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Lionell Yip En Zhi
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124
2
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Adversarial Training for EM Classification Networks
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Eva Brayfindley
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40
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Certified Monotonic Neural Networks
Neural Information Processing Systems (NeurIPS), 2020
Xingchao Liu
Xing Han
Na Zhang
Qiang Liu
278
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Multi-Task Adversarial Attack
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Yuancheng Xu
Xiaoyuan Zhang
Yu Zhang
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200
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Gradient Starvation: A Learning Proclivity in Neural Networks
Neural Information Processing Systems (NeurIPS), 2020
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
538
308
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Extreme Value Preserving Networks
Mingjie Sun
Jianguo Li
Changshui Zhang
AAML
MDE
126
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Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
International Conference on Machine Learning (ICML), 2020
Yuxin Wen
Shuai Li
Kui Jia
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140
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Audio-Visual Event Recognition through the lens of Adversary
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Juncheng Li
Kaixin Ma
Shuhui Qu
Po-Yao (Bernie) Huang
Florian Metze
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140
9
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Adversarial Image Color Transformations in Explicit Color Filter Space
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2020
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Zhuoran Liu
Martha Larson
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357
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Katherine A. Heller
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D. Sculley
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Wei Chen
Tie-Yan Liu
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Jinqi Luo
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239
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Context Dependent Semantic Parsing: A Survey
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218
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