Adversarially Robust Generalization Requires More Data

30 April 2018

Papers citing "Adversarially Robust Generalization Requires More Data"

46 / 146 papers shown

Title
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 19 81 0 15 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 22 29 0 17 May 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise Omar Montasser Surbhi Goel Ilias Diakonikolas Nathan Srebro 13 32 0 15 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 26 56 0 28 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 26 8 0 23 Apr 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 14 246 0 28 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 50 63 0 02 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 24 785 0 26 Feb 2020
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting Pranav Rajpurkar Anirudh Joshi Anuj Pareek Phil Chen Amirhossein Kiani Jeremy Irvin A. Ng M. Lungren LM&MA 11 49 0 26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 26 69 0 25 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 17 0 0 25 Feb 2020
MaxUp: A Simple Way to Improve Generalization of Neural Network Training Chengyue Gong Tongzheng Ren Mao Ye Qiang Liu AAML 14 56 0 20 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 27 64 0 11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 16 34 0 05 Feb 2020
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study Jinlan Fu Pengfei Liu Qi Zhang Xuanjing Huang AI4CE 25 73 0 12 Jan 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 22 107 0 27 Dec 2019
Universal adversarial examples in speech command classification Jon Vadillo Roberto Santana AAML 29 29 0 22 Nov 2019
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? Jingfeng Zhang Bo Han Gang Niu Tongliang Liu Masashi Sugiyama 10 6 0 20 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 24 68 0 06 Nov 2019
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition Mimansa Jaiswal E. Provost 23 72 0 29 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear Classification Xupeng Shi A. Ding AAML 14 3 0 27 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 30 85 0 09 Oct 2019
A Closer Look at Data Bias in Neural Extractive Summarization Models Ming Zhong Danqing Wang Pengfei Liu Xipeng Qiu Xuanjing Huang 40 42 0 30 Sep 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 21 230 0 24 Jul 2019
Adversarial Training Can Hurt Generalization Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang 11 239 0 14 Jun 2019
Lower Bounds for Adversarially Robust PAC Learning Dimitrios I. Diochnos Saeed Mahloujifar Mohammad Mahmoody AAML 13 26 0 13 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 8 129 0 24 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 22 157 0 23 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 17 374 0 30 Apr 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 13 3 0 24 Mar 2019
Interpreting Neural Networks Using Flip Points Roozbeh Yousefzadeh D. O’Leary AAML FAtt 19 17 0 21 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 16 175 0 13 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 22 318 0 29 Jan 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 12 717 0 28 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry K. Ramchandran AAML 11 54 0 24 Jan 2019
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 11 68 0 13 Nov 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 23 64 0 08 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 20 166 0 01 Nov 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 16 171 0 01 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 11 15 0 30 Sep 2018
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 16 109 0 03 Aug 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 62 230 0 25 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 14 368 0 23 May 2018
On Visual Hallmarks of Robustness to Adversarial Malware Alex Huang Abdullah Al-Dujaili Erik Hemberg Una-May O’Reilly AAML 19 7 0 09 May 2018