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2002.11565
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Randomization matters. How to defend against strong adversarial attacks
International Conference on Machine Learning (ICML), 2020
26 February 2020
Rafael Pinot
Raphael Ettedgui
Geovani Rizk
Y. Chevaleyre
Jamal Atif
AAML
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Papers citing
"Randomization matters. How to defend against strong adversarial attacks"
36 / 36 papers shown
Lattice Climber Attack: Adversarial attacks for randomized mixtures of classifiers
Lucas Gnecco-Heredia
Benjamin Négrevergne
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265
0
0
12 Jun 2025
Towards provable probabilistic safety for scalable embodied AI systems
Linxuan He
Qing-Shan Jia
Ang Li
Hongyan Sang
Ling Wang
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Yisen Wang
Peng Wei
Zhongyuan Wang
Henry X. Liu
Shuo Feng
310
1
0
05 Jun 2025
Adversarial Detection with a Dynamically Stable System
Xiaowei Long
Jie Lin
Xiangyuan Yang
AAML
243
0
0
11 Nov 2024
LightPure: Realtime Adversarial Image Purification for Mobile Devices Using Diffusion Models
ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), 2024
Hossein Khalili
Seongbin Park
Vincent Li
Brandan Bright
Ali Payani
Ramana Rao Kompella
Nader Sehatbakhsh
AAML
244
6
0
31 Aug 2024
Understanding Byzantine Robustness in Federated Learning with A Black-box Server
Fangyuan Zhao
Yuexiang Xie
Xuebin Ren
Bolin Ding
Shusen Yang
Yaliang Li
FedML
AAML
304
1
0
12 Aug 2024
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Neural Information Processing Systems (NeurIPS), 2023
Yifei Wang
Liangchen Li
Jiansheng Yang
Zhouchen Lin
Yisen Wang
316
20
0
30 Oct 2023
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks
Neural Information Processing Systems (NeurIPS), 2023
Ao Zhang
Yu Ran
Weixuan Tang
Yuan-Gen Wang
358
19
0
24 Sep 2023
Adversarial attacks for mixtures of classifiers
Lucas Gnecco-Heredia
Benjamin Négrevergne
Y. Chevaleyre
AAML
191
1
0
20 Jul 2023
Towards Optimal Randomized Strategies in Adversarial Example Game
AAAI Conference on Artificial Intelligence (AAAI), 2023
Jiahao Xie
Chao Zhang
Weijie Liu
Wensong Bai
Hui Qian
AAML
173
0
0
29 Jun 2023
How Does Information Bottleneck Help Deep Learning?
International Conference on Machine Learning (ICML), 2023
Kenji Kawaguchi
Zhun Deng
Xu Ji
Jiaoyang Huang
243
115
0
30 May 2023
The Best Defense is a Good Offense: Adversarial Augmentation against Adversarial Attacks
Computer Vision and Pattern Recognition (CVPR), 2023
I. Frosio
Jan Kautz
AAML
308
30
0
23 May 2023
Do we need entire training data for adversarial training?
Vipul Gupta
Apurva Narayan
AAML
254
2
0
10 Mar 2023
On the Role of Randomization in Adversarially Robust Classification
Neural Information Processing Systems (NeurIPS), 2023
Lucas Gnecco-Heredia
Y. Chevaleyre
Benjamin Négrevergne
Laurent Meunier
Muni Sreenivas Pydi
AAML
321
6
0
14 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations
International Conference on Machine Learning (ICML), 2023
Hassan Dbouk
Naresh R Shanbhag
AAML
391
8
0
02 Feb 2023
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning
IEEE Access (IEEE Access), 2022
Ethan Rathbun
Kaleel Mahmood
Sohaib Ahmad
Caiwen Ding
Marten van Dijk
AAML
254
8
0
26 Nov 2022
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Maria-Florina Balcan
Rattana Pukdee
Pradeep Ravikumar
Hongyang R. Zhang
AAML
236
12
0
23 Oct 2022
Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game
Xiao-Shan Gao
Shuang Liu
Lijia Yu
AAML
292
1
0
17 Jul 2022
Metric-Fair Classifier Derandomization
International Conference on Machine Learning (ICML), 2022
Jimmy Wu
Yatong Chen
Yang Liu
FaML
321
5
0
15 Jun 2022
Adversarial Vulnerability of Randomized Ensembles
International Conference on Machine Learning (ICML), 2022
Hassan Dbouk
Naresh R Shanbhag
AAML
231
8
0
14 Jun 2022
Building Robust Ensembles via Margin Boosting
International Conference on Machine Learning (ICML), 2022
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAML
UQCV
210
17
0
07 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis
Raphael Ettedgui
Alexandre Araujo
Rafael Pinot
Y. Chevaleyre
Jamal Atif
AAML
218
3
0
03 Jun 2022
Towards Consistency in Adversarial Classification
Neural Information Processing Systems (NeurIPS), 2022
Laurent Meunier
Raphael Ettedgui
Rafael Pinot
Y. Chevaleyre
Jamal Atif
AAML
179
12
0
20 May 2022
Diffusion Models for Adversarial Purification
International Conference on Machine Learning (ICML), 2022
Weili Nie
Brandon Guo
Yujia Huang
Chaowei Xiao
Arash Vahdat
Anima Anandkumar
WIGM
626
645
0
16 May 2022
The Many Faces of Adversarial Risk
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Muni Sreenivas Pydi
Varun Jog
AAML
215
32
0
22 Jan 2022
A Dynamical System Perspective for Lipschitz Neural Networks
International Conference on Machine Learning (ICML), 2021
Laurent Meunier
Blaise Delattre
Alexandre Araujo
A. Allauzen
321
69
0
25 Oct 2021
When Should You Defend Your Classifier -- A Game-theoretical Analysis of Countermeasures against Adversarial Examples
Maximilian Samsinger
F. Merkle
Pascal Schöttle
Tomás Pevný
AAML
245
4
0
17 Aug 2021
Scalable Optimal Classifiers for Adversarial Settings under Uncertainty
Decision and Game Theory for Security (GameSec), 2021
Patrick Loiseau
Benjamin Roussillon
162
1
0
28 Jun 2021
Adversarial purification with Score-based generative models
International Conference on Machine Learning (ICML), 2021
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
370
194
0
11 Jun 2021
Attacking Adversarial Attacks as A Defense
Boxi Wu
Heng Pan
Li Shen
Jindong Gu
Shuai Zhao
Zhifeng Li
Deng Cai
Xiaofei He
Wei Liu
AAML
249
41
0
09 Jun 2021
Robustifying
ℓ
∞
\ell_\infty
ℓ
∞
Adversarial Training to the Union of Perturbation Models
Ameya D. Patil
Michael Tuttle
Alex Schwing
Naresh R Shanbhag
AAML
257
0
0
31 May 2021
The art of defense: letting networks fool the attacker
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2021
Jinlai Zhang
Lyvjie Chen
Binbin Liu
Bojun Ouyang
Jihong Zhu
Minchi Kuang
Houqing Wang
Yanmei Meng
AAML
3DPC
384
21
0
07 Apr 2021
Mixed Nash Equilibria in the Adversarial Examples Game
International Conference on Machine Learning (ICML), 2021
Laurent Meunier
M. Scetbon
Rafael Pinot
Jamal Atif
Y. Chevaleyre
AAML
254
32
0
13 Feb 2021
Advocating for Multiple Defense Strategies against Adversarial Examples
Alexandre Araujo
Laurent Meunier
Rafael Pinot
Benjamin Négrevergne
AAML
177
10
0
04 Dec 2020
A survey on practical adversarial examples for malware classifiers
Daniel Park
B. Yener
AAML
256
17
0
06 Nov 2020
Robustness Verification for Classifier Ensembles
Dennis Gross
N. Jansen
Guillermo A. Pérez
S. Raaijmakers
AAML
172
8
0
12 May 2020
Adversarial Risk via Optimal Transport and Optimal Couplings
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
Muni Sreenivas Pydi
Varun Jog
329
60
0
05 Dec 2019
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