Unveiling the potential of Graph Neural Networks for robust Intrusion Detection
Authors: David Pujol-Perich, José Suárez-Varela, Albert Cabellos-Aparicio, Pere Barlet-Ros | Published: 2021-07-30
ロバスト性
Principles for Evaluation of AI/ML Model Performance and Robustness
Authors: Olivia Brown, Andrew Curtis, Justin Goodwin | Published: 2021-07-06
Certifiably Robust Interpretation via Renyi Differential Privacy
Authors: Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan | Published: 2021-07-04
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems
Authors: Zixiu Wang, Yiwen Guo, Hu Ding | Published: 2021-06-30 | Updated: 2022-01-21
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization
Authors: Prashnna Kumar Gyawali, Sandesh Ghimire, Linwei Wang | Published: 2020-09-23
Detection of Iterative Adversarial Attacks via Counter Attack
Authors: Matthias Rottmann, Kira Maag, Mathis Peyron, Natasa Krejic, Hanno Gottschalk | Published: 2020-09-23 | Updated: 2021-03-23
Semantics-Preserving Adversarial Training
Authors: Wonseok Lee, Hanbit Lee, Sang-goo Lee | Published: 2020-09-23
Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks
Authors: Boyuan Feng, Yuke Wang, Zheng Wang, Yufei Ding | Published: 2020-09-22
Optimal Provable Robustness of Quantum Classification via Quantum Hypothesis Testing
Authors: Maurice Weber, Nana Liu, Bo Li, Ce Zhang, Zhikuan Zhao | Published: 2020-09-21 | Updated: 2021-05-26
Improving adversarial robustness of deep neural networks by using semantic information
Authors: Lina Wang, Rui Tang, Yawei Yue, Xingshu Chen, Wei Wang, Yi Zhu, Xuemei Zeng | Published: 2020-08-18 | Updated: 2021-06-17