Adversarial Training Versus Weight Decay
Authors: Angus Galloway, Thomas Tanay, Graham W. Taylor | Published: 2018-04-10 | Updated: 2018-07-23
敵対的学習
Bypassing Feature Squeezing by Increasing Adversary Strength
Authors: Yash Sharma, Pin-Yu Chen | Published: 2018-03-27
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning
Authors: Tegjyot Singh Sethi, Mehmed Kantardzic, Lingyu Lyua, Jiashun Chen | Published: 2018-03-24
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Authors: Daniel Jakubovitz, Raja Giryes | Published: 2018-03-23 | Updated: 2019-05-28
Adversarial Defense based on Structure-to-Signal Autoencoders
Authors: Joachim Folz, Sebastian Palacio, Joern Hees, Damian Borth, Andreas Dengel | Published: 2018-03-21
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks
Authors: Octavian Suciu, Radu Mărginean, Yiğitcan Kaya, Hal Daumé III, Tudor Dumitraş | Published: 2018-03-19 | Updated: 2019-03-08
Adversarial Logit Pairing
Authors: Harini Kannan, Alexey Kurakin, Ian Goodfellow | Published: 2018-03-16
Vulnerability of Deep Learning
Authors: Richard Kenway | Published: 2018-03-16
Variance Networks: When Expectation Does Not Meet Your Expectations
Authors: Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, Dmitry Vetrov | Published: 2018-03-10 | Updated: 2019-02-18
Stochastic Activation Pruning for Robust Adversarial Defense
Authors: Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Anima Anandkumar | Published: 2018-03-05