Theoretically Principled Trade-off between Robustness and Accuracy

24 January 2019

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

50 / 605 papers shown

Title
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training Adir Rahamim I. Naeh AAML 35 1 0 16 Mar 2022
LAS-AT: Adversarial Training with Learnable Attack Strategy Xiaojun Jia Yong Zhang Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 47 131 0 13 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 34 47 0 11 Mar 2022
Exploiting the Potential of Datasets: A Data-Centric Approach for Model Robustness Yiqi Zhong Lei Wu Xianming Liu Junjun Jiang AAML 30 9 0 10 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack Ye Liu Yaya Cheng Lianli Gao Xianglong Liu Qilong Zhang Jingkuan Song AAML 45 57 0 10 Mar 2022
Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity Cheng Luo Qinliang Lin Weicheng Xie Bizhu Wu Jinheng Xie Linlin Shen AAML 39 101 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
Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4 William Berrios Arturo Deza MedIm ViT 30 13 0 08 Mar 2022
Robustly-reliable learners under poisoning attacks Maria-Florina Balcan Avrim Blum Steve Hanneke Dravyansh Sharma AAML OOD 26 14 0 08 Mar 2022
Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation Xiaogeng Liu Haoyu Wang Yechao Zhang Fangzhou Wu Shengshan Hu OOD 27 11 0 08 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 15 18 0 03 Mar 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 24 12 0 01 Mar 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 181 68 0 28 Feb 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 46 43 0 27 Feb 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 34 13 0 26 Feb 2022
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning Hao He Kaiwen Zha Dina Katabi AAML 36 33 0 22 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks Yinghua Gao Dongxian Wu Jingfeng Zhang Guanhao Gan Shutao Xia Gang Niu Masashi Sugiyama AAML 32 22 0 22 Feb 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 37 15 0 21 Feb 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 28 0 0 21 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 40 120 0 21 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 100 47 0 20 Feb 2022
Exploring Adversarially Robust Training for Unsupervised Domain Adaptation Shao-Yuan Lo Vishal M. Patel AAML 41 8 0 18 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen Sijia Liu AAML 54 16 0 15 Feb 2022
Adversarial Attacks and Defense Methods for Power Quality Recognition Jiwei Tian Buhong Wang Jing Li Zhen Wang Mete Ozay AAML 28 0 0 11 Feb 2022
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles Ashish Hooda Neal Mangaokar Ryan Feng Kassem Fawaz S. Jha Atul Prakash 35 11 0 11 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial nets Zhenyu Zhu Fabian Latorre Grigorios G. Chrysos V. Cevher 27 10 0 10 Feb 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 25 3 0 05 Feb 2022
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization Xiaojun Xu Jacky Y. Zhang Evelyn Ma Danny Son Oluwasanmi Koyejo Bo-wen Li 20 10 0 03 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 32 4 0 03 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Aleksandrovich Pautov Olesya Kuznetsova Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets 47 5 0 02 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 139 16 0 31 Jan 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 37 15 0 30 Jan 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Mengting Xu Tao Zhang Zhongnian Li Daoqiang Zhang AAML 38 1 0 29 Jan 2022
Efficient and Robust Classification for Sparse Attacks M. Beliaev Payam Delgosha Hamed Hassani Ramtin Pedarsani AAML 27 2 0 23 Jan 2022
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective Jihong Wang Minnan Luo Jundong Li Ziqi Liu Jun Zhou Qinghua Zheng AAML 23 5 0 21 Jan 2022
Transferability in Deep Learning: A Survey Junguang Jiang Yang Shu Jianmin Wang Mingsheng Long OOD 34 101 0 15 Jan 2022
Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions Marwan Omar Soohyeon Choi Daehun Nyang David A. Mohaisen 32 57 0 03 Jan 2022
Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness Hao Yang Min Wang Zhengfei Yu Yun Zhou OOD AAML 22 3 0 01 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 34 10 0 31 Dec 2021
Learning Robust and Lightweight Model through Separable Structured Transformations Xian Wei Yanhui Huang Yang Xu Mingsong Chen Hai Lan Yuanxiang Li Zhongfeng Wang Xuan Tang OOD 24 0 0 27 Dec 2021
Stealthy Attack on Algorithmic-Protected DNNs via Smart Bit Flipping B. Ghavami Seyd Movi Zhenman Fang Lesley Shannon AAML 40 9 0 25 Dec 2021
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? Xinhsuai Dong Anh Tuan Luu Min Lin Shuicheng Yan Hanwang Zhang SILM AAML 25 55 0 22 Dec 2021
Sharpness-Aware Minimization with Dynamic Reweighting Wenxuan Zhou Fangyu Liu Huan Zhang Muhao Chen AAML 31 8 0 16 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 131 0 15 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 28 13 0 14 Dec 2021
Triangle Attack: A Query-efficient Decision-based Adversarial Attack Xiaosen Wang Zeliang Zhang Kangheng Tong Dihong Gong Kun He Zhifeng Li Wei Liu AAML 24 56 0 13 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 34 12 0 12 Dec 2021
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 28 2 0 12 Dec 2021
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri S. Feizi Ramalingam Chellappa OOD AAML 48 24 0 09 Dec 2021