Theoretically Principled Trade-off between Robustness and Accuracy

24 January 2019

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

50 / 583 papers shown

Title
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning Xiaoyang Sean Wang Bo-wen Li Yibo Jacky Zhang B. Kailkhura K. Nahrstedt 18 3 0 15 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 22 11 0 22 Dec 2020
Self-Progressing Robust Training Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 29 9 0 22 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 27 4 0 18 Dec 2020
A Closer Look at the Robustness of Vision-and-Language Pre-trained Models Linjie Li Zhe Gan Jingjing Liu VLM 33 42 0 15 Dec 2020
Composite Adversarial Attacks Xiaofeng Mao YueFeng Chen Shuhui Wang Hang Su Yuan He Hui Xue AAML 33 48 0 10 Dec 2020
Unsupervised Adversarially-Robust Representation Learning on Graphs Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Yizhou Sun SSL AAML OOD 35 36 0 04 Dec 2020
FAT: Federated Adversarial Training Giulio Zizzo Ambrish Rawat M. Sinn Beat Buesser FedML 33 43 0 03 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 28 92 0 30 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 49 8 0 03 Nov 2020
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems Jiawei Zhang Peijun Xiao Ruoyu Sun Zhi-Quan Luo 33 97 0 29 Oct 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 24 57 0 26 Oct 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 227 0 26 Oct 2020
Posterior Differential Regularization with f-divergence for Improving Model Robustness Hao Cheng Xiaodong Liu L. Pereira Yaoliang Yu Jianfeng Gao 248 31 0 23 Oct 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie-jin Yang AAML 41 8 0 23 Oct 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 33 62 0 21 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 680 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 324 0 07 Oct 2020
Adversarial Boot Camp: label free certified robustness in one epoch Ryan Campbell Chris Finlay Adam M. Oberman AAML 25 0 0 05 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 16 108 0 05 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 47 269 0 05 Oct 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi Ma Yuan Yao AAML 37 26 0 28 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 29 11 0 21 Sep 2020
Label Smoothing and Adversarial Robustness Chaohao Fu Hongbin Chen Na Ruan Weijia Jia AAML 16 12 0 17 Sep 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 25 12 0 14 Sep 2020
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 31 23 0 11 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 33 128 0 09 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020
Adversarially Robust Neural Architectures Minjing Dong Yanxi Li Yunhe Wang Chang Xu AAML OOD 42 48 0 02 Sep 2020
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Yanchao Sun Da Huo Furong Huang AAML OffRL OnRL 21 49 0 02 Sep 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 24 19 0 19 Aug 2020
Optimizing Information Loss Towards Robust Neural Networks Philip Sperl Konstantin Böttinger AAML 18 3 0 07 Aug 2020
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases Ren Wang Gaoyuan Zhang Sijia Liu Pin-Yu Chen Jinjun Xiong Meng Wang AAML 33 148 0 31 Jul 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli GAN AAML 28 16 0 29 Jul 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 22 6 0 22 Jul 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 24 23 0 22 Jul 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 590 0 17 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 37 417 0 16 Jul 2020
On Adversarial Robustness: A Neural Architecture Search perspective Chaitanya Devaguptapu Devansh Agarwal Gaurav Mittal Pulkit Gopalani V. Balasubramanian OOD AAML 12 33 0 16 Jul 2020
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training Kai Liang Tan Yasaman Esfandiari Xian Yeow Lee Aakanksha S. Sarkar AAML 26 55 0 14 Jul 2020
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning Feng Wang Chen Zhong M. C. Gursoy Senem Velipasalar AAML 18 8 0 12 Jul 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples S. Goldwasser Adam Tauman Kalai Y. Kalai Omar Montasser AAML 19 38 0 10 Jul 2020
Boundary thickness and robustness in learning models Yaoqing Yang Rekha Khanna Yaodong Yu A. Gholami Kurt Keutzer Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney OOD 18 37 0 09 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 23 57 0 08 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 39 536 0 01 Jul 2020