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
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 21 7 0 09 Feb 2021
Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples Jay Nandy Sudipan Saha W. Hsu M. Lee Xiaosu Zhu AAML 27 3 0 09 Feb 2021
A Real-time Defense against Website Fingerprinting Attacks Shawn Shan A. Bhagoji Haitao Zheng Ben Y. Zhao AAML 14 19 0 08 Feb 2021
Understanding the Interaction of Adversarial Training with Noisy Labels Jianing Zhu Jingfeng Zhang Bo Han Tongliang Liu Gang Niu Hongxia Yang Mohan S. Kankanhalli Masashi Sugiyama AAML 21 27 0 06 Feb 2021
Robust Single-step Adversarial Training with Regularizer Lehui Xie Yaopeng Wang Jianwei Yin Ximeng Liu AAML 28 1 0 05 Feb 2021
TAD: Trigger Approximation based Black-box Trojan Detection for AI Xinqiao Zhang Huili Chen F. Koushanfar AAML 12 14 0 03 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 76 473 0 02 Feb 2021
Towards Speeding up Adversarial Training in Latent Spaces Yaguan Qian Qiqi Shao Tengteng Yao Bin Wang Shouling Ji Shaoning Zeng Zhaoquan Gu Wassim Swaileh AAML 14 4 0 01 Feb 2021
Adversarial Learning with Cost-Sensitive Classes Hao Shen Sihong Chen Ran Wang Xizhao Wang AAML 14 11 0 29 Jan 2021
Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attacks Jia-Wei Liu Yaochu Jin AAML OOD 10 36 0 16 Jan 2021
Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds B. Georgiev L. Franken Mayukh Mukherjee AAML 21 1 0 15 Jan 2021
Adversarial Machine Learning in Text Analysis and Generation I. Alsmadi AAML 21 5 0 14 Jan 2021
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks Arno Blaas Stephen J. Roberts BDL AAML 60 2 0 07 Jan 2021
A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning Ahmadreza Jeddi M. Shafiee A. Wong AAML 25 37 0 25 Dec 2020
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 17 11 0 22 Dec 2020
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead Maurizio Capra Beatrice Bussolino Alberto Marchisio Guido Masera Maurizio Martina Muhammad Shafique BDL 56 140 0 21 Dec 2020
RAILS: A Robust Adversarial Immune-inspired Learning System Ren Wang Tianqi Chen Stephen Lindsly A. Rehemtulla Alfred Hero I. Rajapakse AAML 12 7 0 18 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 22 4 0 18 Dec 2020
A Closer Look at the Robustness of Vision-and-Language Pre-trained Models Linjie Li Zhe Gan Jingjing Liu VLM 33 42 0 15 Dec 2020
Amata: An Annealing Mechanism for Adversarial Training Acceleration Nanyang Ye Qianxiao Li Xiao-Yun Zhou Zhanxing Zhu AAML 24 15 0 15 Dec 2020
DSRNA: Differentiable Search of Robust Neural Architectures Ramtin Hosseini Xingyi Yang P. Xie OOD AAML 29 50 0 11 Dec 2020
Using Feature Alignment Can Improve Clean Average Precision and Adversarial Robustness in Object Detection Weipeng Xu Hongcheng Huang Shaoyou Pan ObjD 31 7 0 08 Dec 2020
Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy Shashi Kant Gupta OOD 17 3 0 08 Dec 2020
Detecting Trojaned DNNs Using Counterfactual Attributions Karan Sikka Indranil Sur Susmit Jha Anirban Roy Ajay Divakaran AAML 9 12 0 03 Dec 2020
FAT: Federated Adversarial Training Giulio Zizzo Ambrish Rawat M. Sinn Beat Buesser FedML 27 43 0 03 Dec 2020
Content-Adaptive Pixel Discretization to Improve Model Robustness Ryan Feng Wu-chi Feng Atul Prakash AAML 20 0 0 03 Dec 2020
Visually Imperceptible Adversarial Patch Attacks on Digital Images Yaguan Qian Jiamin Wang Bin Wang Xiang Ling Zhaoquan Gu Chunming Wu Wassim Swaileh AAML 31 2 0 02 Dec 2020
Adversarial Robustness Across Representation Spaces Pranjal Awasthi George Yu Chun-Sung Ferng Andrew Tomkins Da-Cheng Juan OOD AAML 16 11 0 01 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 17 92 0 30 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu-Lin Liu Liwei Wang Jiaya Jia OOD AAML 19 124 0 23 Nov 2020
A Neuro-Inspired Autoencoding Defense Against Adversarial Perturbations Can Bakiskan Metehan Cekic Ahmet Dundar Sezer Upamanyu Madhow AAML 26 0 0 21 Nov 2020
Effective, Efficient and Robust Neural Architecture Search Zhixiong Yue Baijiong Lin Xiaonan Huang Yu Zhang AAML 23 19 0 19 Nov 2020
Contextual Fusion For Adversarial Robustness Aiswarya Akumalla S. Haney M. Bazhenov AAML 22 1 0 18 Nov 2020
Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks Maungmaung Aprilpyone Hitoshi Kiya FedML 17 1 0 16 Nov 2020
Adversarial Image Color Transformations in Explicit Color Filter Space Zhengyu Zhao Zhuoran Liu Martha Larson AAML 24 12 0 12 Nov 2020
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks Leo Schwinn An Nguyen René Raab Dario Zanca Bjoern M. Eskofier Daniel Tenbrinck Martin Burger AAML 14 8 0 05 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 46 8 0 03 Nov 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 16 57 0 26 Oct 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 226 0 26 Oct 2020
Contrastive Learning with Adversarial Examples Chih-Hui Ho Nuno Vasconcelos SSL 19 140 0 22 Oct 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data Lingkai Kong Haoming Jiang Yuchen Zhuang Jie Lyu T. Zhao Chao Zhang OODD 24 26 0 22 Oct 2020
Robust Optimization as Data Augmentation for Large-scale Graphs Kezhi Kong Bernard Ghanem Mucong Ding Zuxuan Wu Chen Zhu Guohao Li Gavin Taylor Tom Goldstein 106 74 0 19 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 231 677 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training Zichao Li Liyuan Liu Chengyu Dong Jingbo Shang AAML 14 8 0 15 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 11 107 0 05 Oct 2020
Do Wider Neural Networks Really Help Adversarial Robustness? Boxi Wu Jinghui Chen Deng Cai Xiaofei He Quanquan Gu AAML 6 95 0 03 Oct 2020
Efficient Robust Training via Backward Smoothing Jinghui Chen Yu Cheng Zhe Gan Quanquan Gu Jingjing Liu AAML 16 40 0 03 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 21 57 0 02 Oct 2020