| Promptst: Prompt-enhanced spatio-temporal multi-attribute prediction Z Zhang, X Zhao, Q Liu, C Zhang, Q Ma, W Wang, H Zhao, Y Wang, Z Liu Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 5 | 2023 |
| Rethinking sensors modeling: Hierarchical information enhanced traffic forecasting Q Ma, Z Zhang, X Zhao, H Li, H Zhao, Y Wang, Z Liu, W Wang Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 4 | 2023 |
| STRec: Sparse transformer for sequential recommendations C Li, Y Wang, Q Liu, X Zhao, W Wang, Y Wang, L Zou, W Fan, Q Li Proceedings of the 17th ACM Conference on Recommender Systems, 101-111, 2023 | 6 | 2023 |
| Linrec: Linear attention mechanism for long-term sequential recommender systems L Liu, L Cai, C Zhang, X Zhao, J Gao, W Wang, Y Lv, W Fan, Y Wang, ... Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 16 | 2023 |
| AutoDPQ: Automated Differentiable Product Quantization for Embedding Compression X Gan, Y Wang, X Zhao, W Wang, Y Wang, Z Liu Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | | 2023 |
| Recommender systems in the era of large language models (llms) W Fan, Z Zhao, J Li, Y Liu, X Mei, Y Wang, J Tang, Q Li arXiv preprint arXiv:2307.02046, 2023 | 126 | 2023 |
| Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? J Li, H Shomer, J Ding, Y Wang, Y Ma, N Shah, J Tang, D Yin Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 15 | 2023 |
| Trustworthy ai: A computational perspective H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu, A Jain, J Tang ACM Transactions on Intelligent Systems and Technology 14 (1), 1-59, 2022 | 190 | 2022 |
| Test-time training for graph neural networks Y Wang, C Li, W Jin, R Li, J Zhao, J Tang, X Xie arXiv preprint arXiv:2210.08813, 2022 | 12 | 2022 |
| A comprehensive survey on trustworthy recommender systems W Fan, X Zhao, X Chen, J Su, J Gao, L Wang, Q Liu, Y Wang, H Xu, ... arXiv preprint arXiv:2209.10117, 2022 | 33 | 2022 |
| Graph neural networks for multimodal single-cell data integration H Wen, J Ding, W Jin, Y Wang, Y Xie, J Tang Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 43 | 2022 |
| House: Knowledge graph embedding with householder parameterization R Li, J Zhao, C Li, D He, Y Wang, Y Liu, H Sun, S Wang, W Deng, Y Shen, ... International conference on machine learning, 13209-13224, 2022 | 41 | 2022 |
| An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering Y Wang, C Li, Z Liu, M Li, J Tang, X Xie, L Chen, PS Yu ACM Transactions on Information Systems, 2021 | 19 | 2021 |
| Gophormer: Ego-graph transformer for node classification J Zhao, C Li, Q Wen, Y Wang, Y Liu, H Sun, X Xie, Y Ye arXiv preprint arXiv:2110.13094, 2021 | 54 | 2021 |
| Graph representation learning: foundations, methods, applications and systems W Jin, Y Ma, Y Wang, X Liu, J Tang, Y Cen, J Qiu, J Tang, C Shi, Y Ye, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 3 | 2021 |
| Localized Graph Collaborative Filtering Y Wang, C Li, M Li, W Jin, Y Liu, H Sun, X Xie, J Tang Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), 2021 | 14 | 2021 |
| Elastic graph neural networks X Liu, W Jin, Y Ma, Y Li, H Liu, Y Wang, M Yan, J Tang International Conference on Machine Learning, 6837-6849, 2021 | 108 | 2021 |
| Node similarity preserving graph convolutional networks W Jin, T Derr, Y Wang, Y Ma, Z Liu, J Tang Proceedings of the 14th ACM international conference on web search and data …, 2021 | 218 | 2021 |
| Adversarial attacks and defenses on graphs W Jin, Y Li, H Xu, Y Wang, S Ji, C Aggarwal, J Tang ACM SIGKDD Explorations Newsletter 22 (2), 19-34, 2021 | 167 | 2021 |
| Graph Neural Networks: Models and Advances Y Wang, W Jin, Y Ma, J Tang | | 2021 |
Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State University在 msu.edu 的电子邮件经过验证
