Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Authors: Battista Biggio, Fabio Roli | Published: 2017-12-08 | Updated: 2018-07-19
Adversarial Learning
Improving Network Robustness against Adversarial Attacks with Compact Convolution
Authors: Rajeev Ranjan, Swami Sankaranarayanan, Carlos D. Castillo, Rama Chellappa | Published: 2017-12-03 | Updated: 2018-03-22
Where Classification Fails, Interpretation Rises
Authors: Chanh Nguyen, Georgi Georgiev, Yujie Ji, Ting Wang | Published: 2017-12-02
Machine vs Machine: Minimax-Optimal Defense Against Adversarial Examples
Authors: Jihun Hamm, Akshay Mehra | Published: 2017-11-12 | Updated: 2018-06-27
Intriguing Properties of Adversarial Examples
Authors: Ekin D. Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le | Published: 2017-11-08
Adversarial Frontier Stitching for Remote Neural Network Watermarking
Authors: Erwan Le Merrer, Patrick Perez, Gilles Trédan | Published: 2017-11-06 | Updated: 2019-08-07
Implicit Weight Uncertainty in Neural Networks
Authors: Nick Pawlowski, Andrew Brock, Matthew C. H. Lee, Martin Rajchl, Ben Glocker | Published: 2017-11-03 | Updated: 2018-05-25
Certifying Some Distributional Robustness with Principled Adversarial Training
Authors: Aman Sinha, Hongseok Namkoong, Riccardo Volpi, John Duchi | Published: 2017-10-29 | Updated: 2020-05-01
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features
Authors: Liang Tong, Bo Li, Chen Hajaj, Chaowei Xiao, Ning Zhang, Yevgeniy Vorobeychik | Published: 2017-08-28 | Updated: 2019-05-10
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Authors: Taesik Na, Jong Hwan Ko, Saibal Mukhopadhyay | Published: 2017-08-08 | Updated: 2018-03-17