Unlabeled Data Improves Adversarial Robustness

31 May 2019

Papers citing "Unlabeled Data Improves Adversarial Robustness"

50 / 225 papers shown

Title
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli Fahad Shahbaz Khan AAML 28 1 0 30 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 29 5 0 15 Dec 2022
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images Pei Liu Luping Ji Feng Ye Bo Fu 29 27 0 13 Dec 2022
Robust Perception through Equivariance Chengzhi Mao Lingyu Zhang Abhishek Joshi Junfeng Yang Hongya Wang Carl Vondrick BDL AAML 31 7 0 12 Dec 2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Jiaheng Zhang AAML 39 11 0 23 Nov 2022
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization Zifa Wang Nan Ding Tomer Levinboim Xi Chen Radu Soricut AAML 37 5 0 22 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 45 7 0 21 Nov 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 49 10 0 19 Nov 2022
Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting Peng-Fei Hou Jie Han Xingyu Li AAML OOD 23 11 0 26 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 41 13 0 21 Oct 2022
Effective Targeted Attacks for Adversarial Self-Supervised Learning Minseon Kim Hyeonjeong Ha Sooel Son Sung Ju Hwang AAML 39 3 0 19 Oct 2022
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation Jun-Kun Wang Andre Wibisono 37 7 0 18 Oct 2022
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers Gaurav Kumar Nayak Ruchit Rawal Anirban Chakraborty 19 3 0 17 Oct 2022
Visual Prompting for Adversarial Robustness Aochuan Chen P. Lorenz Yuguang Yao Pin-Yu Chen Sijia Liu VLM VPVLM 40 32 0 12 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 36 24 0 12 Oct 2022
A2: Efficient Automated Attacker for Boosting Adversarial Training Zhuoer Xu Guanghui Zhu Changhua Meng Shiwen Cui ZhenZhe Ying Weiqiang Wang GU Ming Yihua Huang AAML 36 13 0 07 Oct 2022
Strength-Adaptive Adversarial Training Chaojian Yu Dawei Zhou Li Shen Jun Yu Bo Han Biwei Huang Nannan Wang Tongliang Liu OOD 17 2 0 04 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 38 30 0 03 Oct 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 69 0 15 Sep 2022
On the interplay of adversarial robustness and architecture components: patches, convolution and attention Francesco Croce Matthias Hein 43 6 0 14 Sep 2022
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey Yanbei Chen Massimiliano Mancini Xiatian Zhu Zeynep Akata 47 114 0 24 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models Dong Huang Qi Bu Yuhao Qing Haowen Pi Sen Wang Heming Cui OOD AAML 37 0 0 17 Aug 2022
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction Jiacheng Zhu Jielin Qiu Zhuolin Yang Douglas Weber M. Rosenberg Emerson Liu Bo-wen Li Ding Zhao OOD 33 13 0 02 Aug 2022
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang Kang Zhang Chenshuang Zhang Axi Niu Jiu Feng Chang D. Yoo In So Kweon SSL 40 24 0 22 Jul 2022
Contrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility Rohit Gupta Naveed Akhtar Ajmal Mian M. Shah AAML SSL 28 5 0 22 Jul 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift Ananya Kumar Tengyu Ma Percy Liang Aditi Raghunathan UQCV OODD OOD 49 38 0 18 Jul 2022
Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations H. Malik Shahina Kunhimon Muzammal Naseer Salman Khan Fahad Shahbaz Khan AAML 33 8 0 18 Jul 2022
Adversarial Contrastive Learning via Asymmetric InfoNCE Qiying Yu Jieming Lou Xianyuan Zhan Qizhang Li W. Zuo Yang Liu Jingjing Liu AAML 41 23 0 18 Jul 2022
Landscape Learning for Neural Network Inversion Ruoshi Liu Chen-Guang Mao Purva Tendulkar Hongya Wang Carl Vondrick 38 8 0 17 Jun 2022
Double Sampling Randomized Smoothing Linyi Li Jiawei Zhang Tao Xie Bo-wen Li AAML 17 23 0 16 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale Gaoyuan Zhang Songtao Lu Yihua Zhang Xiangyi Chen Pin-Yu Chen Quanfu Fan Lee Martie L. Horesh Min-Fong Hong Sijia Liu OOD 35 12 0 13 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 48 15 0 07 Jun 2022
Attack-Agnostic Adversarial Detection Jiaxin Cheng Mohamed Hussein J. Billa Wael AbdAlmageed AAML 28 0 0 01 Jun 2022
Guided Diffusion Model for Adversarial Purification Jinyi Wang Zhaoyang Lyu Dahua Lin Bo Dai Hongfei Fu DiffM 196 83 0 30 May 2022
Robust Weight Perturbation for Adversarial Training Chaojian Yu Bo Han Biwei Huang Li Shen Shiming Ge Bo Du Tongliang Liu AAML 27 33 0 30 May 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction Ruochen Jiao Xiangguo Liu Takami Sato Qi Alfred Chen Qi Zhu AAML 43 20 0 27 May 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 49 9 0 23 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 32 26 0 16 May 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 37 11 0 13 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 37 0 0 04 May 2022
Measuring the False Sense of Security Carlos Gomes AAML 27 0 0 10 Apr 2022
Using Multiple Self-Supervised Tasks Improves Model Robustness Matthew Lawhon Chengzhi Mao Junfeng Yang AAML SSL 19 4 0 07 Apr 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 40 15 0 05 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters Paul Gavrikov J. Keuper AAML 24 31 0 29 Mar 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 26 33 0 27 Mar 2022
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 19 6 0 24 Mar 2022
Leveraging Adversarial Examples to Quantify Membership Information Leakage Ganesh Del Grosso Hamid Jalalzai Georg Pichler C. Palamidessi Pablo Piantanida MIACV 41 21 0 17 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack Ye Liu Yaya Cheng Lianli Gao Xianglong Liu Qilong Zhang Jingkuan Song AAML 43 57 0 10 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He Wang Yunfeng Diao Zichang Tan G. Guo AAML 53 10 0 09 Mar 2022