Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

3 March 2020

Matthias Hein

Papers citing "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

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Title
Parameterizing Activation Functions for Adversarial Robustness Sihui Dai Saeed Mahloujifar Prateek Mittal AAML 42 32 0 11 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 56 18 0 07 Oct 2021
Introducing the DOME Activation Functions Mohamed E. Hussein Wael AbdAlmageed 30 1 0 30 Sep 2021
Modeling Adversarial Noise for Adversarial Training Dawei Zhou Nannan Wang Bo Han Tongliang Liu AAML 38 15 0 21 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Katie Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 49 12 0 11 Sep 2021
Training Meta-Surrogate Model for Transferable Adversarial Attack Yunxiao Qin Yuanhao Xiong Jinfeng Yi Cho-Jui Hsieh AAML 15 18 0 05 Sep 2021
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks Landan Seguin A. Ndirango Neeli Mishra SueYeon Chung Tyler Lee OOD 25 2 0 26 Aug 2021
A Hierarchical Assessment of Adversarial Severity Guillaume Jeanneret Juan Pérez Pablo Arbeláez AAML 20 2 0 26 Aug 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 24 73 0 20 Aug 2021
Towards Understanding the Generative Capability of Adversarially Robust Classifiers Yao Zhu Jiacheng Ma Jiacheng Sun Zewei Chen Rongxin Jiang Zhenguo Li AAML 18 21 0 20 Aug 2021
Neural Architecture Dilation for Adversarial Robustness Yanxi Li Zhaohui Yang Yunhe Wang Chang Xu AAML 38 23 0 16 Aug 2021
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning Hong Wang Yuefan Deng Shinjae Yoo Haibin Ling Yuewei Lin AAML 27 15 0 13 Aug 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lió Marco Maggini S. Melacci 37 69 0 11 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense Duhun Hwang Eunjung Lee Wonjong Rhee AAML 167 14 0 14 Jul 2021
Towards Robust General Medical Image Segmentation Laura Alexandra Daza Juan C. Pérez Pablo Arbelaez OOD 28 25 0 09 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 24 4 0 06 Jul 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization Sungyoon Lee Hoki Kim Jaewook Lee AAML 32 52 0 06 Jul 2021
HODA: Hardness-Oriented Detection of Model Extraction Attacks A. M. Sadeghzadeh Amir Mohammad Sobhanian F. Dehghan R. Jalili MIACV 25 7 0 21 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 27 21 0 17 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 23 23 0 12 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 33 22 0 08 Jun 2021
Reveal of Vision Transformers Robustness against Adversarial Attacks Ahmed Aldahdooh W. Hamidouche Olivier Déforges ViT 15 56 0 07 Jun 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 14 58 0 21 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David Wagner Trevor Darrell AAML 26 26 0 18 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 33 4 0 18 May 2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability Luke Chang Katharina Dost Kaiqi Zhao Ambra Demontis Fabio Roli Gillian Dobbie Jörg Simon Wicker AAML 19 2 0 02 May 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 33 44 0 19 Apr 2021
Removing Adversarial Noise in Class Activation Feature Space Dawei Zhou N. Wang Chunlei Peng Xinbo Gao Xiaoyu Wang Jun Yu Tongliang Liu AAML 30 28 0 19 Apr 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele AAML MQ 24 18 0 16 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
Adversarial Robustness under Long-Tailed Distribution Tong Wu Ziwei Liu Qingqiu Huang Yu Wang Dahua Lin 21 76 0 06 Apr 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 20 217 0 31 Mar 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 33 137 0 29 Mar 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip Torr Guohao Li AAML 31 26 0 26 Mar 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 30 8 0 22 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 35 25 0 20 Mar 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 41 57 0 08 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 25 1 0 04 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 269 0 02 Mar 2021
Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training Dorjan Hitaj Giulio Pagnotta I. Masi L. Mancini OOD AAML 20 22 0 02 Mar 2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints Maura Pintor Fabio Roli Wieland Brendel Battista Biggio AAML 48 70 0 25 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 30 10 0 15 Feb 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 20 29 0 13 Feb 2021
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression Masanori Yamada Sekitoshi Kanai Tomoharu Iwata Tomokatsu Takahashi Yuki Yamanaka Hiroshi Takahashi Atsutoshi Kumagai AAML 16 9 0 05 Feb 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 22 11 0 22 Dec 2020
Learning Energy-Based Models With Adversarial Training Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 33 9 0 11 Dec 2020