| Subspace adversarial training T Li, Y Wu, S Chen, K Fang, X Huang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 52 | 2022 |
| Adversarial attack on attackers: Post-process to mitigate black-box score-based query attacks S Chen, Z Huang, Q Tao, Y Wu, C Xie, X Huang Advances in Neural Information Processing Systems 35, 14929-14943, 2022 | 18 | 2022 |
| Towards robust neural networks via orthogonal diversity K Fang, Q Tao, Y Wu, T Li, J Cai, F Cai, X Huang, J Yang Pattern Recognition 149, 110281, 2024 | 7 | 2024 |
| Trainable weight averaging: Efficient training by optimizing historical solutions T Li, Z Huang, Q Tao, Y Wu, X Huang The Eleventh International Conference on Learning Representations, 2022 | 5 | 2022 |
| Unifying gradients to improve real-world robustness for deep networks Y Wu, S Chen, K Fang, X Huang arXiv preprint arXiv:2208.06228, 2022 | 3 | 2022 |
| Efficient generalization improvement guided by random weight perturbation T Li, W Yan, Z Lei, Y Wu, K Fang, M Yang, X Huang arXiv preprint arXiv:2211.11489, 2022 | 2 | 2022 |
| On multi-head ensemble of smoothed classifiers for certified robustness K Fang, Q Tao, Y Wu, T Li, X Huang, J Yang arXiv preprint arXiv:2211.10882, 2022 | 2 | 2022 |
| Low-Dimensional Gradient Helps Out-of-Distribution Detection Y Wu, T Li, X Cheng, J Yang, X Huang arXiv preprint arXiv:2310.17163, 2023 | 1 | 2023 |
| Online Continual Learning via Logit Adjusted Softmax Z Huang, T Li, C Yuan, Y Wu, X Huang arXiv preprint arXiv:2311.06460, 2023 | | 2023 |
Xiaolin Huang (黄晓霖)Professor, Shanghai Jiao Tong University在 sjtu.edu.cn 的电子邮件经过验证
