| Understanding negative sampling in graph representation learning Z Yang, M Ding, C Zhou, H Yang, J Zhou, J Tang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 138 | 2020 |
| Mixgcf: An improved training method for graph neural network-based recommender systems T Huang, Y Dong, M Ding, Z Yang, W Feng, X Wang, J Tang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 98 | 2021 |
| Stam: A spatiotemporal aggregation method for graph neural network-based recommendation Z Yang, M Ding, B Xu, H Yang, J Tang Proceedings of the ACM Web Conference 2022, 3217-3228, 2022 | 20 | 2022 |
| Region or global a principle for negative sampling in graph-based recommendation Z Yang, M Ding, X Zou, J Tang, B Xu, C Zhou, H Yang IEEE Transactions on Knowledge and Data Engineering, 2022 | 13 | 2022 |
| Gpt can solve mathematical problems without a calculator Z Yang, M Ding, Q Lv, Z Jiang, Z He, Y Guo, J Bai, J Tang arXiv preprint arXiv:2309.03241, 2023 | 2 | 2023 |
| BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs Z Yang, T Huang, M Ding, Y Dong, R Ying, Y Cen, Y Geng, J Tang arXiv preprint arXiv:2306.03355, 2023 | 2 | 2023 |
| ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation W Wang, Z Yang, B Xu, J Li, Y Sun Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 1 | 2023 |
Ming DingTsinghua University, Zhipu AI在 mails.tsinghua.edu.cn 的电子邮件经过验证
