Unlabeled Data Improves Adversarial Robustness

31 May 2019

Papers citing "Unlabeled Data Improves Adversarial Robustness"

50 / 193 papers shown

Title
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better MingWei Zhou Xiaobing Pei AAML 152 0 0 30 Mar 2025
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data Lilin Zhang Chengpei Wu Ning Yang 36 0 0 14 Mar 2025
Long-tailed Adversarial Training with Self-Distillation Seungju Cho Hongsin Lee Changick Kim AAML TTA 185 0 0 09 Mar 2025
HALO: Robust Out-of-Distribution Detection via Joint Optimisation Hugo Lyons Keenan S. Erfani Christopher Leckie OODD 209 0 0 27 Feb 2025
Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach Nicolas Atienza Christophe Labreuche Johanne Cohen Michele Sebag OODD AAML 144 0 0 20 Jan 2025
A Brain-Inspired Regularizer for Adversarial Robustness Elie Attias C. Pehlevan D. Obeid AAML OOD 20 0 0 04 Oct 2024
Towards Universal Certified Robustness with Multi-Norm Training Enyi Jiang Gagandeep Singh Gagandeep Singh AAML 60 1 0 03 Oct 2024
Adversarial Robustification via Text-to-Image Diffusion Models Daewon Choi Jongheon Jeong Huiwon Jang Jinwoo Shin DiffM 44 1 0 26 Jul 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 39 0 0 26 Jun 2024
Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das Inderjit S Dhillon Alessandro Epasto Adel Javanmard Jieming Mao Vahab Mirrokni Sujay Sanghavi Peilin Zhong 50 1 0 17 Jun 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 48 2 0 27 May 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 45 0 0 03 May 2024
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape Tiejin Chen Wenwang Huang Linsey Pang Dongsheng Luo Hua Wei OOD 46 0 0 09 Mar 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 33 6 0 11 Feb 2024
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations Enyi Jiang Gagandeep Singh AAML 30 1 0 09 Feb 2024
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views Yuji Roh Qingyun Liu Huan Gui Zhe Yuan Yujin Tang ... Liang Liu Shuchao Bi Lichan Hong Ed H. Chi Zhe Zhao 43 1 0 07 Feb 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing Xiaofeng Lin Qifan Song Yi Tian Xu Belinda Zeng Guang Cheng SSL 23 0 0 26 Jan 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training Shruthi Gowda Bahram Zonooz Elahe Arani AAML 31 2 0 26 Jan 2024
Indirect Gradient Matching for Adversarial Robust Distillation Hongsin Lee Seungju Cho Changick Kim AAML FedML 53 2 0 06 Dec 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 34 10 0 28 Oct 2023
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin Chaojian Yu Bo Han Tongliang Liu 31 7 0 13 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 40 1 0 06 Oct 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants M. Losch David Stutz Bernt Schiele Mario Fritz 14 4 0 12 Sep 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 33 2 0 01 Aug 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 29 12 0 10 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 27 1 0 29 Jun 2023
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning Jungtaek Kim 32 1 0 24 May 2023
Collaborative Development of NLP models Fereshte Khani Marco Tulio Ribeiro 30 2 0 20 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 37 49 0 18 May 2023
Utility Theory of Synthetic Data Generation Shi Xu W. Sun Guang Cheng 25 5 0 17 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 28 4 0 13 May 2023
ESimCSE Unsupervised Contrastive Learning Jointly with UDA Semi-Supervised Learning for Large Label System Text Classification Mode Ruan Lu Zhou Hangcheng Ran Meng Zhao Jin Qin JiaoYu Wei Feng Wang ChenZi 37 0 0 19 Apr 2023
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser Astha Verma A. Subramanyam Siddhesh Bangar Naman Lal R. Shah Shiníchi Satoh 34 4 0 13 Apr 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 30 4 0 06 Apr 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 15 0 0 29 Mar 2023
Generalist: Decoupling Natural and Robust Generalization Hongjun Wang Yisen Wang OOD AAML 49 14 0 24 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 41 34 0 19 Mar 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance Amine Bennouna Ryan Lucas Bart P. G. Van Parys 35 10 0 03 Mar 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 21 7 0 21 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 2023
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule Maor Ivgi Oliver Hinder Y. Carmon ODL 26 56 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 19 2 0 06 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 33 10 0 03 Feb 2023
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks Jona Klemenc Holger Trittenbach AAML 24 1 0 28 Jan 2023
Data Augmentation Alone Can Improve Adversarial Training Lin Li Michael W. Spratling 16 50 0 24 Jan 2023
Towards Understanding How Self-training Tolerates Data Backdoor Poisoning Soumyadeep Pal Ren Wang Yuguang Yao Sijia Liu 45 6 0 20 Jan 2023
Beckman Defense A. V. Subramanyam OOD AAML 34 0 0 04 Jan 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli F. Khan AAML 22 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
Robust Perception through Equivariance Chengzhi Mao Lingyu Zhang Abhishek Joshi Junfeng Yang Hongya Wang Carl Vondrick BDL AAML 29 7 0 12 Dec 2022