| Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation J Yu, H Yin, X Xia, T Chen, L Cui, QVH Nguyen The 45th International ACM SIGIR Conference on Research and Development in …, 2022 | 654 | 2022 |
| Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation X Xia, H Yin, J Yu, Q Wang, L Cui, X Zhang Proceedings of the AAAI conference on artificial intelligence, 2021 | 558 | 2021 |
| Self-supervised multi-channel hypergraph convolutional network for social recommendation J Yu, H Yin, J Li, Q Wang, NQV Hung, X Zhang Proceedings of the Web Conference (WWW), 413-424, 2021 | 496 | 2021 |
| Self-supervised learning for recommender systems: A survey J Yu, H Yin, X Xia, T Chen, J Li, Z Huang IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 | 324 | 2023 |
| Socially-Aware Self-Supervised Tri-Training for Recommendation J Yu, H Yin, M Gao, X Xia, X Zhang, NQV Hung ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2021 | 213 | 2021 |
| XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation J Yu, X Xia, T Chen, L Cui, NQV Hung, H Yin IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 | 202 | 2023 |
| Enhancing social recommendation with adversarial graph convolutional networks J Yu, H Yin, J Li, M Gao, Z Huang, L Cui IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 | 196 | 2020 |
| Self-Supervised Graph Co-Training for Session-based Recommendation X Xia, H Yin, J Yu, Y Shao, L Cui ACM International Conference on Information and Knowledge Management (CIKM), 2021 | 195 | 2021 |
| Adaptive implicit friends identification over heterogeneous network for social recommendation J Yu, M Gao, J Li, H Yin, H Liu ACM International Conference on Information and Knowledge Management (CIKM), 2018 | 144 | 2018 |
| Fast-adapting and privacy-preserving federated recommender system Q Wang, H Yin, T Chen, J Yu, A Zhou, X Zhang The VLDB Journal 31 (5), 877-896, 2022 | 141 | 2022 |
| Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation J Zhang, M Gao, J Yu, L Guo, J Li, H Yin ACM International Conference on Information and Knowledge Management (CIKM), 2021 | 140 | 2021 |
| Generating reliable friends via adversarial training to improve social recommendation J Yu, M Gao, H Yin, J Li, C Gao, Q Wang IEEE International Conference on Data Mining (ICDM), 768-777, 2019 | 108 | 2019 |
| Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective M Gao, J Zhang, J Yu, J Li, J Wen, Q Xiong Information Sciences, 1166-1185, 2021 | 81 | 2021 |
| On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation X Xia, H Yin, J Yu, Q Wang, G Xu, NQV Hung Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 56 | 2022 |
| A social recommender based on factorization and distance metric learning J Yu, M Gao, W Rong, Y Song, Q Xiong IEEE Access 5, 21557-21566, 2017 | 40 | 2017 |
| Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack F Wu, M Gao, J Yu, Z Wang, K Liu, X Wange Information Sciences, 683-701, 2021 | 36 | 2021 |
| Efficient On-Device Session-Based Recommendation X Xia, J Yu, Q Wang, C Yang, QVH Nguyen, H Yin ACM Transactions on Information Systems (TOIS), 2023 | 35 | 2023 |
| Collaborative shilling detection bridging factorization and user embedding T Dou, J Yu, Q Xiong, M Gao, Y Song, Q Fang International Conference on Collaborative Computing: Networking …, 2017 | 29 | 2017 |
| Hybrid attacks on model-based social recommender systems J Yu, M Gao, W Rong, W Li, Q Xiong, J Wen Physica A: Statistical Mechanics and its Applications 483, 171-181, 2017 | 29 | 2017 |
| A minimax game for generative and discriminative sample models for recommendation Z Wang, M Gao, X Wang, J Yu, J Wen, Q Xiong Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2019 | 25 | 2019 |
Hongzhi YinProfessor and ARC Future Fellow, University of Queensland在 uq.edu.au 的电子邮件经过验证