| Don’t waste your bits! squeeze activations and gradients for deep neural networks via tinyscript F Fu, Y Hu, Y He, J Jiang, Y Shao, C Zhang, B Cui International Conference on Machine Learning, 3304-3314, 2020 | 55 | 2020 |
| Towards understanding the data dependency of mixup-style training M Chidambaram, X Wang, Y Hu, C Wu, R Ge The Tenth International Conference on Learning Representations. 2022., 2021 | 18 | 2021 |
| Actor-critic is implicitly biased towards high entropy optimal policies Y Hu, Z Ji, M Telgarsky The Tenth International Conference on Learning Representations. 2022., 2021 | 13 | 2021 |
| Revisiting scalarization in multi-task learning: a theoretical perspective Y Hu, R Xian, Q Wu, Q Fan, L Yin, H Zhao Thirty-seventh Conference on Neural Information Processing Systems. 2023., 2023 | 10 | 2023 |
| Understanding the impact of adversarial robustness on accuracy disparity Y Hu, F Wu, H Zhang, H Zhao International Conference on Machine Learning, 13679-13709, 2023 | 8 | 2023 |
| Is vertical logistic regression privacy-preserving? a comprehensive privacy analysis and beyond Y Hu, T Cai, J Shan, S Tang, C Cai, E Song, B Li, D Song arXiv preprint arXiv:2207.09087, 2022 | 6 | 2022 |
| HPL-ViT: A Unified Perception Framework for Heterogeneous Parallel LiDARs in V2V Y Liu, B Sun, Y Li, Y Hu, FY Wang IEEE International Conference on Robotics and Automation (ICRA 2024), 2024 | 3 | 2024 |
| SoK: Privacy-Preserving Data Synthesis Y Hu, F Wu, Q Li, Y Long, GM Garrido, C Ge, B Ding, D Forsyth, B Li, ... IEEE Symposium on Security and Privacy (S&P 2024), 2024 | 3 | 2024 |
