Theoretically Principled Trade-off between Robustness and Accuracy

24 January 2019

Papers citing "Theoretically Principled Trade-off between Robustness and Accuracy"

50 / 574 papers shown

Title
Fairness-aware Regression Robust to Adversarial Attacks Yulu Jin Lifeng Lai FaML OOD 29 4 0 04 Nov 2022
Adversarial Defense via Neural Oscillation inspired Gradient Masking Chunming Jiang Yilei Zhang AAML 29 2 0 04 Nov 2022
Maximum Likelihood Distillation for Robust Modulation Classification Javier Maroto Gérôme Bovet P. Frossard AAML 18 5 0 01 Nov 2022
ARDIR: Improving Robustness using Knowledge Distillation of Internal Representation Tomokatsu Takahashi Masanori Yamada Yuuki Yamanaka Tomoya Yamashita 20 0 0 01 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
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 24 5 0 26 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 24 7 0 25 Oct 2022
Adversarial Pretraining of Self-Supervised Deep Networks: Past, Present and Future Guo-Jun Qi M. Shah SSL 23 8 0 23 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 36 13 0 21 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness Chester Holtz Tsui-Wei Weng Gal Mishne OOD 35 4 0 20 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
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 33 22 0 18 Oct 2022
Towards Generating Adversarial Examples on Mixed-type Data Han Xu Menghai Pan Zhimeng Jiang Huiyuan Chen Xiaoting Li Mahashweta Das Hao Yang AAML SILM 18 0 0 17 Oct 2022
ODG-Q: Robust Quantization via Online Domain Generalization Chaofan Tao Ngai Wong MQ 39 1 0 17 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yi Mo Dongxian Wu Yifei Wang Yiwen Guo Yisen Wang ViT 45 52 0 14 Oct 2022
Composite Learning for Robust and Effective Dense Predictions Menelaos Kanakis Thomas E. Huang David Brüggemann Feng Yu Luc Van Gool SSL 39 3 0 13 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
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 47 18 0 11 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 33 5 0 11 Oct 2022
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints Yinpeng Dong Shouwei Ruan Hang Su Cai Kang Xingxing Wei Junyi Zhu AAML 32 49 0 08 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
Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEs Prashant Pandey Aleti Vardhan Mustafa Chasmai Tanuj Sur Brejesh Lall AAML 27 9 0 07 Oct 2022
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition Luke Rowe Benjamin Thérien Krzysztof Czarnecki Hongyang R. Zhang OOD 27 0 0 05 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
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022
PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition Qidong Huang Xiaoyi Dong Dongdong Chen Hang Zhou Weiming Zhang Kui Zhang Gang Hua Nenghai Yu 3DPC 32 12 0 16 Sep 2022
Enhance the Visual Representation via Discrete Adversarial Training Xiaofeng Mao YueFeng Chen Ranjie Duan Yao Zhu Gege Qi Shaokai Ye Xiaodan Li Rong Zhang Hui Xue 44 31 0 16 Sep 2022
A Light Recipe to Train Robust Vision Transformers Edoardo Debenedetti Vikash Sehwag Prateek Mittal ViT 32 69 0 15 Sep 2022
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser Steve Hanneke Nathan Srebro 29 17 0 15 Sep 2022
Improving Robust Fairness via Balance Adversarial Training Chunyu Sun Chenye Xu Chengyuan Yao Siyuan Liang Yichao Wu Ding Liang XiangLong Liu Aishan Liu 23 11 0 15 Sep 2022
Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora Mehmet Fatih Şahin Fanghui Liu Grigorios G. Chrysos V. Cevher 23 5 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
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples Nuo Xu Kaleel Mahmood Haowen Fang Ethan Rathbun Caiwen Ding Wujie Wen AAML 34 12 0 07 Sep 2022
Bag of Tricks for FGSM Adversarial Training Zichao Li Li Liu Zeyu Wang Yuyin Zhou Cihang Xie AAML 33 6 0 06 Sep 2022
Adversarial Robustness for Tabular Data through Cost and Utility Awareness Klim Kireev B. Kulynych Carmela Troncoso AAML 26 16 0 27 Aug 2022
Why is the video analytics accuracy fluctuating, and what can we do about it? Sibendu Paul Kunal Rao G. Coviello Murugan Sankaradas Oliver Po Y. C. Hu S. Chakradhar AAML 14 3 0 23 Aug 2022
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance Bahjat Kawar Roy Ganz Michael Elad DiffM 29 38 0 18 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 32 0 0 17 Aug 2022
AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning Tianxing Zhang Hanzhou Wu Xiaofeng Lu Guangling Sun AAML 27 4 0 08 Aug 2022
Improving Adversarial Robustness via Mutual Information Estimation Dawei Zhou Nannan Wang Xinbo Gao Bo Han Xiaoyu Wang Yibing Zhan Tongliang Liu AAML 16 15 0 25 Jul 2022
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer Yingyi Chen Xiaoke Shen Yahui Liu Qinghua Tao Johan A. K. Suykens AAML ViT 33 22 0 25 Jul 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 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
AugRmixAT: A Data Processing and Training Method for Improving Multiple Robustness and Generalization Performance Xiaoliang Liu S. Furao Jian Zhao Changhai Nie AAML 15 1 0 21 Jul 2022
Adversarial Contrastive Learning via Asymmetric InfoNCE Qiying Yu Jieming Lou Xianyuan Zhan Qizhang Li W. Zuo Yang Liu Jingjing Liu AAML 36 23 0 18 Jul 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models Tsachi Blau Roy Ganz Bahjat Kawar Alex M. Bronstein Michael Elad AAML DiffM 27 26 0 17 Jul 2022
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations Tianlong Chen Peihao Wang Zhiwen Fan Zhangyang Wang 36 55 0 04 Jul 2022
Removing Batch Normalization Boosts Adversarial Training Haotao Wang Aston Zhang Shuai Zheng Xingjian Shi Mu Li Zhangyang Wang 40 41 0 04 Jul 2022
Exact Spectral Norm Regularization for Neural Networks Anton Johansson Claes Strannegård Niklas Engsner P. Mostad AAML 25 2 0 27 Jun 2022