FAT: Federated Adversarial Training
Authors: Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser | Published: 2020-12-03
敵対的訓練
An Analysis of Robustness of Non-Lipschitz Networks
Authors: Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang | Published: 2020-10-13 | Updated: 2023-04-18
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Authors: Han Xu, Xiaorui Liu, Yaxin Li, Anil K. Jain, Jiliang Tang | Published: 2020-10-13 | Updated: 2021-05-18
Crafting Adversarial Examples for Deep Learning Based Prognostics (Extended Version)
Authors: Gautam Raj Mode, Khaza Anuarul Hoque | Published: 2020-09-21 | Updated: 2020-09-28
Feature Distillation With Guided Adversarial Contrastive Learning
Authors: Tao Bai, Jinnan Chen, Jun Zhao, Bihan Wen, Xudong Jiang, Alex Kot | Published: 2020-09-21
Adversarial Training with Stochastic Weight Average
Authors: Joong-Won Hwang, Youngwan Lee, Sungchan Oh, Yuseok Bae | Published: 2020-09-21
A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks
Authors: Ruoxin Chen, Jie Li, Chentao Wu, Bin Sheng, Ping Li | Published: 2020-09-18 | Updated: 2020-10-13
Robust Deep Learning Ensemble against Deception
Authors: Wenqi Wei, Ling Liu | Published: 2020-09-14
Input Hessian Regularization of Neural Networks
Authors: Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft | Published: 2020-09-14
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses
Authors: Ambar Pal, René Vidal | Published: 2020-09-14 | Updated: 2020-11-11