Provably Robust Adversarial Examples
Authors: Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin Vechev | Published: 2020-07-23 | Updated: 2022-03-17
Hide-and-Seek Privacy Challenge
Authors: James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar | Published: 2020-07-23 | Updated: 2020-07-24
Private Post-GAN Boosting
Authors: Marcel Neunhoeffer, Zhiwei Steven Wu, Cynthia Dwork | Published: 2020-07-23 | Updated: 2021-03-25
Robust Machine Learning via Privacy/Rate-Distortion Theory
Authors: Ye Wang, Shuchin Aeron, Adnan Siraj Rakin, Toshiaki Koike-Akino, Pierre Moulin | Published: 2020-07-22 | Updated: 2021-05-18
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review
Authors: Yansong Gao, Bao Gia Doan, Zhi Zhang, Siqi Ma, Jiliang Zhang, Anmin Fu, Surya Nepal, Hyoungshick Kim | Published: 2020-07-21 | Updated: 2020-08-02
How Does Data Augmentation Affect Privacy in Machine Learning?
Authors: Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu | Published: 2020-07-21 | Updated: 2021-02-26
Scaling Polyhedral Neural Network Verification on GPUs
Authors: Christoph Müller, François Serre, Gagandeep Singh, Markus Püschel, Martin Vechev | Published: 2020-07-20 | Updated: 2021-05-18
Adversarial Immunization for Certifiable Robustness on Graphs
Authors: Shuchang Tao, Huawei Shen, Qi Cao, Liang Hou, Xueqi Cheng | Published: 2020-07-19 | Updated: 2021-08-25
Neural Networks with Recurrent Generative Feedback
Authors: Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar | Published: 2020-07-17 | Updated: 2020-11-10
Learning perturbation sets for robust machine learning
Authors: Eric Wong, J. Zico Kolter | Published: 2020-07-16 | Updated: 2020-10-08