Are adversarial examples inevitable?
Authors: Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein | Published: 2018-09-06 | Updated: 2020-02-03
ロバスト性分析
Bridging machine learning and cryptography in defence against adversarial attacks
Authors: Olga Taran, Shideh Rezaeifar, Slava Voloshynovskiy | Published: 2018-09-05
Adversarial Attacks on Node Embeddings via Graph Poisoning
Authors: Aleksandar Bojchevski, Stephan Günnemann | Published: 2018-09-04 | Updated: 2019-05-27
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Authors: Sanli Tang, Xiaolin Huang, Mingjian Chen, Chengjin Sun, Jie Yang | Published: 2018-09-03 | Updated: 2019-07-22
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Authors: Cong Liao, Haoti Zhong, Anna Squicciarini, Sencun Zhu, David Miller | Published: 2018-08-30
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust
Authors: Chris Finlay, Jeff Calder, Bilal Abbasi, Adam Oberman | Published: 2018-08-28 | Updated: 2019-09-12
Stochastic Combinatorial Ensembles for Defending Against Adversarial Examples
Authors: George A. Adam, Petr Smirnov, David Duvenaud, Benjamin Haibe-Kains, Anna Goldenberg | Published: 2018-08-20 | Updated: 2018-09-08
Mitigation of Adversarial Attacks through Embedded Feature Selection
Authors: Ziyi Bao, Luis Muñoz-González, Emil C. Lupu | Published: 2018-08-16
Mitigating Sybils in Federated Learning Poisoning
Authors: Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh | Published: 2018-08-14 | Updated: 2020-07-15
Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks
Authors: Fan Yang, Zhiyuan Chen | Published: 2018-08-10