Fast is better than free: Revisiting adversarial training

12 January 2020

J. Zico Kolter

Papers citing "Fast is better than free: Revisiting adversarial training"

50 / 733 papers shown

Title
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 2021
Analysis and Applications of Class-wise Robustness in Adversarial Training Qi Tian Kun Kuang Ke Jiang Fei Wu Yisen Wang AAML 20 46 0 29 May 2021
Deep Repulsive Prototypes for Adversarial Robustness A. Serban E. Poll Joost Visser OOD 22 3 0 26 May 2021
Skew Orthogonal Convolutions Sahil Singla S. Feizi 21 66 0 24 May 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 A. Wagner Trevor Darrell AAML 26 26 0 18 May 2021
Real-time Detection of Practical Universal Adversarial Perturbations Kenneth T. Co Luis Muñoz-González Leslie Kanthan Emil C. Lupu AAML 30 6 0 16 May 2021
Understanding Catastrophic Overfitting in Adversarial Training Peilin Kang Seyed-Mohsen Moosavi-Dezfooli AAML 18 16 0 06 May 2021
This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks Adrian Hoffmann Claudio Fanconi Rahul Rade Jonas Köhler 22 63 0 05 May 2021
A Finer Calibration Analysis for Adversarial Robustness Pranjal Awasthi Anqi Mao M. Mohri Yutao Zhong AAML 49 30 0 04 May 2021
Calibration and Consistency of Adversarial Surrogate Losses Pranjal Awasthi Natalie Frank Anqi Mao M. Mohri Yutao Zhong AAML 23 46 0 19 Apr 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 33 44 0 19 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
Universal Adversarial Training with Class-Wise Perturbations Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 17 26 0 07 Apr 2021
The art of defense: letting networks fool the attacker Jinlai Zhang Lyvjie Chen Binbin Liu Bojun Ouyang Jihong Zhu Minchi Kuang Houqing Wang Yanmei Meng AAML 3DPC 17 15 0 07 Apr 2021
Adversarial Robustness under Long-Tailed Distribution Tong Wu Ziwei Liu Qingqiu Huang Yu Wang Dahua Lin 21 76 0 06 Apr 2021
Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification S. Silva Arun Das I. Scarff Peyman Najafirad AAML 20 1 0 05 Apr 2021
Reliably fast adversarial training via latent adversarial perturbation Geon Yeong Park Sang Wan Lee AAML 12 25 0 04 Apr 2021
Defending Against Image Corruptions Through Adversarial Augmentations D. A. Calian Florian Stimberg Olivia Wiles Sylvestre-Alvise Rebuffi András Gyorgy Timothy A. Mann Sven Gowal AAML 17 41 0 02 Apr 2021
Domain Invariant Adversarial Learning Matan Levi Idan Attias A. Kontorovich AAML OOD 34 11 0 01 Apr 2021
Robustness Certification for Point Cloud Models Tobias Lorenz Anian Ruoss Mislav Balunović Gagandeep Singh Martin Vechev 3DPC 32 26 0 30 Mar 2021
Improving robustness against common corruptions with frequency biased models Tonmoy Saikia Cordelia Schmid Thomas Brox OOD 18 40 0 30 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
ZeroGrad : Mitigating and Explaining Catastrophic Overfitting in FGSM Adversarial Training Zeinab Golgooni Mehrdad Saberi Masih Eskandar M. Rohban AAML 11 14 0 29 Mar 2021
Adversarial Attacks are Reversible with Natural Supervision Chengzhi Mao Mia Chiquer Hao Wang Junfeng Yang Carl Vondrick BDL AAML 13 54 0 26 Mar 2021
THAT: Two Head Adversarial Training for Improving Robustness at Scale Zuxuan Wu Tom Goldstein L. Davis Ser-Nam Lim AAML GAN 21 1 0 25 Mar 2021
A Variational Inequality Approach to Bayesian Regression Games Wenshuo Guo Michael I. Jordan Tianyi Lin 20 5 0 24 Mar 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 30 8 0 22 Mar 2021
Natural Perturbed Training for General Robustness of Neural Network Classifiers Sadaf Gulshad A. Smeulders OOD AAML 19 2 0 21 Mar 2021
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack Ashkan Esmaeili Marzieh Edraki Nazanin Rahnavard M. Shah Ajmal Saeed Mian AAML 30 2 0 19 Mar 2021
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles G. Cantareira R. Mello F. Paulovich AAML 24 9 0 18 Mar 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry Yingqi Liu Guangyu Shen Guanhong Tao Zhenting Wang Shiqing Ma Xinming Zhang AAML 30 8 0 16 Mar 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan V. Oseledets 11 2 0 15 Mar 2021
Internal Wasserstein Distance for Adversarial Attack and Defense Jincheng Li Shuhai Zhang Jiezhang Cao Jian Chen Mingkui Tan Yang Xiang AAML 24 4 0 13 Mar 2021
Transfer Learning-Based Model Protection With Secret Key Maungmaung Aprilpyone Hitoshi Kiya FedML 11 5 0 05 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 23 1 0 04 Mar 2021
On the effectiveness of adversarial training against common corruptions Klim Kireev Maksym Andriushchenko Nicolas Flammarion AAML 11 101 0 03 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 23 90 0 02 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Mind the box: $l_1$ -APGD for sparse adversarial attacks on image classifiers Francesco Croce Matthias Hein AAML 47 54 0 01 Mar 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 13 9 0 24 Feb 2021
Adversarial Robustness with Non-uniform Perturbations Ece Naz Erdemir Jeffrey Bickford Luca Melis Sergul Aydore AAML 22 26 0 24 Feb 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang Kaidi Xu Sijia Liu Pin-Yu Chen Tsui-Wei Weng Chuang Gan Meng Wang AAML 18 46 0 20 Feb 2021
Improving Hierarchical Adversarial Robustness of Deep Neural Networks A. Ma Aladin Virmaux Kevin Scaman Juwei Lu AAML 18 5 0 17 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 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
Exploring Adversarial Robustness of Deep Metric Learning Thomas Kobber Panum Z. Wang Pengyu Kan Earlence Fernandes S. Jha AAML 14 7 0 14 Feb 2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons Bohang Zhang Tianle Cai Zhou Lu Di He Liwei Wang OOD 37 49 0 10 Feb 2021
Backdoor Scanning for Deep Neural Networks through K-Arm Optimization Guangyu Shen Yingqi Liu Guanhong Tao Shengwei An Qiuling Xu Shuyang Cheng Shiqing Ma Xinming Zhang AAML 30 117 0 09 Feb 2021
Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 20 13 0 09 Feb 2021