| Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning S Fu, F He, Y Liu, L Shen, D Tao International Conference on Learning Representations, 2022 | 87* | 2022 |
| Artificial neural variability for deep learning: On overfitting, noise memorization, and catastrophic forgetting Z Xie, F He, S Fu, I Sato, D Tao, M Sugiyama Neural computation 33 (8), 2163-2192, 2021 | 64 | 2021 |
| Knowledge Removal in Sampling-based Bayesian Inference S Fu, F He, D Tao International Conference on Learning Representations, 2022 | 33 | 2022 |
| Bayesian inference forgetting S Fu, F He, Y Xu, D Tao arXiv preprint arXiv:2101.06417, 2021 | 14 | 2021 |
| Robustness, privacy, and generalization of adversarial training F He, S Fu, B Wang, D Tao arXiv preprint arXiv:2012.13573, 2020 | 11 | 2020 |
| Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach S Fu, D Wang International Conference on Learning Representations, 2024 | 1 | 2024 |
| "Short-length" Adversarial Training Helps LLMs Defend "Long-length" Jailbreak Attacks: Theoretical and Empirical Evidence S Fu, L Ding, D Wang arXiv preprint arXiv:2502.04204, 2025 | | 2025 |
| Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services S Fu, X Sun, K Qing, T Zheng, D Wang arXiv preprint arXiv:2408.02814, 2024 | | 2024 |
Dacheng TaoNanyang Technological UniversityПотвърден имейл адрес: ntu.edu.sg