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Theoretically Principled Trade-off between Robustness and Accuracy

24 January 2019

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

37 / 837 papers shown

Title
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 107 351 0 14 Jun 2019
Towards Compact and Robust Deep Neural Networks Vikash Sehwag Shiqi Wang Prateek Mittal Suman Jana AAML 82 40 0 14 Jun 2019
Adversarial Training Can Hurt Generalization Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang 89 244 0 14 Jun 2019
Intriguing properties of adversarial training at scale Cihang Xie Alan Yuille AAML 72 68 0 10 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 74 37 0 09 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 92 43 0 07 Jun 2019
Inductive Bias of Gradient Descent based Adversarial Training on Separable Data Yan Li Ethan X. Fang Huan Xu T. Zhao 92 16 0 07 Jun 2019
A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization Tyler Sypherd Mario Díaz J. Cava Gautam Dasarathy Peter Kairouz Lalitha Sankar 67 29 0 05 Jun 2019
Do Image Classifiers Generalize Across Time? Vaishaal Shankar Achal Dave Rebecca Roelofs Deva Ramanan Benjamin Recht Ludwig Schmidt 142 83 0 05 Jun 2019
Architecture Selection via the Trade-off Between Accuracy and Robustness Zhun Deng Cynthia Dwork Jialiang Wang Yao-Min Zhao AAML 98 3 0 04 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 98 158 0 03 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 130 754 0 31 May 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 97 335 0 31 May 2019
Functional Adversarial Attacks Cassidy Laidlaw Soheil Feizi AAML 100 185 0 29 May 2019
High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks Haohan Wang Xindi Wu Pengcheng Yin Eric Xing 81 526 0 28 May 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 54 121 0 28 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 80 99 0 25 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 88 248 0 24 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 123 161 0 23 May 2019
Adversarially Robust Distillation Micah Goldblum Liam H. Fowl Soheil Feizi Tom Goldstein AAML 85 213 0 23 May 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle Dinghuai Zhang Tianyuan Zhang Yiping Lu Zhanxing Zhu Bin Dong AAML 130 362 0 02 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 139 1,255 0 29 Apr 2019
Bridging Adversarial Robustness and Gradient Interpretability Beomsu Kim Junghoon Seo Taegyun Jeon AAML 84 40 0 27 Mar 2019
Attribution-driven Causal Analysis for Detection of Adversarial Examples Susmit Jha Sunny Raj S. Fernandes Sumit Kumar Jha S. Jha Gunjan Verma B. Jalaeian A. Swami AAML 75 17 0 14 Mar 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 Feb 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 113 344 0 21 Feb 2019
Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps Beomsu Kim Junghoon Seo Seunghyun Jeon Jamyoung Koo J. Choe Taegyun Jeon FAtt 74 70 0 13 Feb 2019
Collaborative Sampling in Generative Adversarial Networks Yuejiang Liu Parth Kothari Alexandre Alahi TTA 128 17 0 02 Feb 2019
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 112 274 0 06 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 41 1 0 05 Dec 2018
Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks Jianyu Wang Haichao Zhang OOD AAML 87 119 0 26 Nov 2018
Attention, Please! Adversarial Defense via Activation Rectification and Preservation Shangxi Wu Jitao Sang Kaiyuan Xu Jiaming Zhang Jian Yu AAML 52 7 0 24 Nov 2018
Learning to Defend by Learning to Attack Haoming Jiang Zhehui Chen Yuyang Shi Bo Dai T. Zhao 93 22 0 03 Nov 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 117 350 0 10 Sep 2018
Adversarial Vision Challenge Wieland Brendel Jonas Rauber Alexey Kurakin Nicolas Papernot Behar Veliqi M. Salathé Sharada Mohanty Matthias Bethge AAML 79 58 0 06 Aug 2018
BUSIS: A Benchmark for Breast Ultrasound Image Segmentation Min Xian Yingtao Zhang H. Cheng Fei Xu Kuan Huang Boyu Zhang Jianrui Ding C. Ning Ying Wang 69 62 0 09 Jan 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 109 174 0 26 Dec 2017