Adversarial Training is a Form of Data-dependent Operator Norm Regularization
Authors: Kevin Roth, Yannic Kilcher, Thomas Hofmann | Published: 2019-06-04 | Updated: 2020-10-23
Adversarial Training
Simple Black-box Adversarial Attacks
Authors: Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger | Published: 2019-05-17 | Updated: 2019-08-15
On Norm-Agnostic Robustness of Adversarial Training
Authors: Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin | Published: 2019-05-15
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning
Authors: Devinder Kumar, Ibrahim Ben-Daya, Kanav Vats, Jeffery Feng, Graham Taylor and, Alexander Wong | Published: 2019-04-21
Adversarial Out-domain Examples for Generative Models
Authors: Dario Pasquini, Marco Mingione, Massimo Bernaschi | Published: 2019-03-07 | Updated: 2019-05-13
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier
Authors: Guanxiong Liu, Issa Khalil, Abdallah Khreishah | Published: 2019-03-06
Excessive Invariance Causes Adversarial Vulnerability
Authors: Jörn-Henrik Jacobsen, Jens Behrmann, Richard Zemel, Matthias Bethge | Published: 2018-11-01 | Updated: 2020-07-12
Logit Pairing Methods Can Fool Gradient-Based Attacks
Authors: Marius Mosbach, Maksym Andriushchenko, Thomas Trost, Matthias Hein, Dietrich Klakow | Published: 2018-10-29 | Updated: 2019-03-12
Rademacher Complexity for Adversarially Robust Generalization
Authors: Dong Yin, Kannan Ramchandran, Peter Bartlett | Published: 2018-10-29 | Updated: 2020-07-29
Detection based Defense against Adversarial Examples from the Steganalysis Point of View
Authors: Jiayang Liu, Weiming Zhang, Yiwei Zhang, Dongdong Hou, Yujia Liu, Hongyue Zha, Nenghai Yu | Published: 2018-06-21 | Updated: 2018-12-24