Using Single-Step Adversarial Training to Defend Iterative Adversarial Examples
Authors: Guanxiong Liu, Issa Khalil, Abdallah Khreishah | Published: 2020-02-22 | Updated: 2020-02-27
敵対的訓練
Robustness from Simple Classifiers
Authors: Sharon Qian, Dimitris Kalimeris, Gal Kaplun, Yaron Singer | Published: 2020-02-21
Adversarial Detection and Correction by Matching Prediction Distributions
Authors: Giovanni Vacanti, Arnaud Van Looveren | Published: 2020-02-21
A Bayes-Optimal View on Adversarial Examples
Authors: Eitan Richardson, Yair Weiss | Published: 2020-02-20 | Updated: 2021-03-17
Boosting Adversarial Training with Hypersphere Embedding
Authors: Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu, Hang Su | Published: 2020-02-20 | Updated: 2020-11-25
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
Authors: Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi | Published: 2020-02-11 | Updated: 2020-08-15
Adversarial Robustness for Code
Authors: Pavol Bielik, Martin Vechev | Published: 2020-02-11 | Updated: 2020-08-15
Improving the affordability of robustness training for DNNs
Authors: Sidharth Gupta, Parijat Dube, Ashish Verma | Published: 2020-02-11 | Updated: 2020-04-30
Square Attack: a query-efficient black-box adversarial attack via random search
Authors: Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion, Matthias Hein | Published: 2019-11-29 | Updated: 2020-07-29
A Useful Taxonomy for Adversarial Robustness of Neural Networks
Authors: Leslie N. Smith | Published: 2019-10-23