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
Improving the Robustness of Deep Convolutional Neural Networks Through Feature Learning Jin Ding Jie-Chao Zhao Yongyang Sun Ping Tan Ji-en Ma You-tong Fang AAML 24 1 0 11 Mar 2023
Do we need entire training data for adversarial training? Vipul Gupta Apurva Narayan AAML 23 1 0 10 Mar 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks Spencer Frei Gal Vardi Peter L. Bartlett Nathan Srebro 34 17 0 02 Mar 2023
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression Junho Kim Byung-Kwan Lee Yonghyun Ro CML AAML 20 18 0 02 Mar 2023
Defending against Adversarial Audio via Diffusion Model Shutong Wu Jiong Wang Wei Ping Weili Nie Chaowei Xiao DiffM 27 25 0 02 Mar 2023
FLINT: A Platform for Federated Learning Integration Ewen N. Wang Ajaykumar Kannan Yuefeng Liang Boyi Chen Mosharaf Chowdhury 33 24 0 24 Feb 2023
Less is More: Data Pruning for Faster Adversarial Training Yize Li Pu Zhao X. Lin B. Kailkhura Ryan Goldh AAML 15 9 0 23 Feb 2023
Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-fitting Perspective Zhengbao He Tao Li Sizhe Chen X. Huang AAML 46 4 0 23 Feb 2023
Masking and Mixing Adversarial Training Hiroki Adachi Tsubasa Hirakawa Takayoshi Yamashita H. Fujiyoshi Yasunori Ishii Kazuki Kozuka AAML 6 1 0 16 Feb 2023
Regret-Based Defense in Adversarial Reinforcement Learning Roman Belaire Pradeep Varakantham Thanh Nguyen David Lo AAML 23 2 0 14 Feb 2023
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization Hamidreza Almasi Harshit Mishra Balajee Vamanan Sathya Ravi FedML 22 0 0 12 Feb 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 27 35 0 10 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 18 208 0 09 Feb 2023
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection Xilie Xu Jingfeng Zhang Feng Liu Masashi Sugiyama Mohan S. Kankanhalli AAML 19 15 0 08 Feb 2023
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks Salah Ghamizi Jingfeng Zhang Maxime Cordy Mike Papadakis Masashi Sugiyama Yves Le Traon AAML 17 2 0 06 Feb 2023
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks Shashank Agnihotri Steffen Jung M. Keuper AAML 26 21 0 04 Feb 2023
Certified Robust Control under Adversarial Perturbations Jinghan Yang Hunmin Kim Wenbin Wan N. Hovakimyan Yevgeniy Vorobeychik AAML 14 1 0 04 Feb 2023
Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization Bo-Han Kung Shang-Tse Chen AAML 17 0 0 01 Feb 2023
Improving Adversarial Transferability with Scheduled Step Size and Dual Example Zeliang Zhang Peihan Liu Xiaosen Wang Chenliang Xu AAML 21 3 0 30 Jan 2023
Uncovering Adversarial Risks of Test-Time Adaptation Tong Wu Feiran Jia Xiangyu Qi Jiachen T. Wang Vikash Sehwag Saeed Mahloujifar Prateek Mittal AAML TTA 23 9 0 29 Jan 2023
Exploring the Effect of Multi-step Ascent in Sharpness-Aware Minimization Hoki Kim Jinseong Park Yujin Choi Woojin Lee Jaewook Lee 15 9 0 27 Jan 2023
DODEM: DOuble DEfense Mechanism Against Adversarial Attacks Towards Secure Industrial Internet of Things Analytics Onat Gungor Tajana Simunic Baris Aksanli AAML 11 0 0 23 Jan 2023
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference Souvik Kundu Shun Lu Yuke Zhang Jacqueline Liu P. Beerel 6 29 0 23 Jan 2023
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation Utkarsh Nath Yancheng Wang Yingzhen Yang AAML 19 2 0 19 Jan 2023
Phase-shifted Adversarial Training Yeachan Kim Seongyeon Kim Ihyeok Seo Bonggun Shin AAML OOD 24 0 0 12 Jan 2023
RobArch: Designing Robust Architectures against Adversarial Attacks Sheng-Hsuan Peng Weilin Xu Cory Cornelius Kevin Li Rahul Duggal Duen Horng Chau Jason Martin AAML 21 5 0 08 Jan 2023
Beckman Defense A. V. Subramanyam OOD AAML 34 0 0 04 Jan 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 39 2 0 03 Jan 2023
Generalizable Black-Box Adversarial Attack with Meta Learning Fei Yin Yong Zhang Baoyuan Wu Yan Feng Jingyi Zhang Yanbo Fan Yujiu Yang AAML 24 27 0 01 Jan 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli F. Khan AAML 20 1 0 30 Dec 2022
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán Gérome Bovet Gregorio Martínez Pérez AAML 27 17 0 30 Dec 2022
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 31 75 0 29 Dec 2022
Certifying Safety in Reinforcement Learning under Adversarial Perturbation Attacks Junlin Wu Hussein Sibai Yevgeniy Vorobeychik AAML 23 0 0 28 Dec 2022
Provable Robust Saliency-based Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie AAML FAtt 27 0 0 28 Dec 2022
Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective Shihua Huang Zhichao Lu Kalyanmoy Deb Vishnu Naresh Boddeti OOD 19 41 0 21 Dec 2022
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 18 27 0 21 Dec 2022
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization Bairu Hou Jinghan Jia Yihua Zhang Guanhua Zhang Yang Zhang Sijia Liu Shiyu Chang SILM AAML 11 20 0 19 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 27 5 0 15 Dec 2022
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection P. Lorenz M. Keuper J. Keuper AAML 11 7 0 13 Dec 2022
Robust Perception through Equivariance Chengzhi Mao Lingyu Zhang Abhishek Joshi Junfeng Yang Hongya Wang Carl Vondrick BDL AAML 29 7 0 12 Dec 2022
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David A. Wagner AAML 29 14 0 12 Dec 2022
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 21 38 0 11 Dec 2022
Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization Lin Li Michael W. Spratling AAML 21 34 0 09 Dec 2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou Jun Huang AAML FedML 34 0 0 05 Dec 2022
CSTAR: Towards Compact and STructured Deep Neural Networks with Adversarial Robustness Huy Phan Miao Yin Yang Sui Bo Yuan S. Zonouz AAML GNN 16 8 0 04 Dec 2022
Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations Hong-Ming Chiu Richard Y. Zhang AAML 12 2 0 30 Nov 2022
Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection Kunlan Xiang Xing Zhang Jinwen She Jinpeng Liu Haohan Wang Shiqi Deng Shancheng Jiang OOD MedIm 29 5 0 30 Nov 2022
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning Xiaoyue Duan Guoliang Kang Runqi Wang Shumin Han Shenjun Xue Tian Wang Baochang Zhang 21 2 0 28 Nov 2022
Supervised Contrastive Prototype Learning: Augmentation Free Robust Neural Network Iordanis Fostiropoulos Laurent Itti 26 1 0 26 Nov 2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Ke Tang AAML 31 11 0 23 Nov 2022