| Position awareness modeling with knowledge distillation for CTR prediction C Liu, Y Li, J Zhu, F Teng, X Zhao, C Peng, Z Lin, J Shao Proceedings of the 16th ACM Conference on Recommender Systems, 562-566, 2022 | 6 | 2022 |
| Dynamic parameterized network for CTR prediction J Zhu, C Liu, P Wang, X Zhao, G Chen, J Jin, C Peng, Z Lin, J Shao arXiv preprint arXiv:2111.04983, 2021 | 3 | 2021 |
| Confidence ranking for CTR prediction J Zhu, C Liu, P Wang, X Zhao, Z Lin, J Shao Companion Proceedings of the ACM Web Conference 2023, 437-441, 2023 | 2 | 2023 |
| Rethinking position bias modeling with knowledge distillation for CTR prediction C Liu, Y Li, J Zhu, X Zhao, C Peng, Z Lin, J Shao arXiv preprint arXiv:2204.00270, 2022 | 2 | 2022 |
| Generalize for Future: Slow and Fast Trajectory Learning for CTR Prediction J Zhu, C Liu, X Jiang, C Peng, Z Lin, J Shao Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 428-436, 2024 | | 2024 |
| Training via Confidence Ranking J Zhu | | 2022 |
Congcong LiuHKUST, ECE在 connect.ust.hk 的电子邮件经过验证
Congcong LiuHKUST, ECE在 connect.ust.hk 的电子邮件经过验证