| ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks L Qu, H Zhu, R Zheng, Y Shi, H Yin KDD 2021, 2021 | 80 | 2021 |
| Continuous-time link prediction via temporal dependent graph neural network L Qu, H Zhu, Q Duan, Y Shi WWW 2020, 2020 | 67 | 2020 |
| Automl for deep recommender systems: A survey R Zheng, L Qu, B Cui, Y Shi, H Yin ACM Transactions on Information Systems 41 (4), 1-38, 2023 | 57 | 2023 |
| Semi-decentralized Federated Ego Graph Learning for Recommendation L Qu, N Tang, R Zheng, QVH Nguyen, Z Huang, Y Shi, H Yin WWW 2023, 2023 | 32 | 2023 |
| Single-shot Embedding Dimension Search in Recommender System L Qu, Y Ye, N Tang, L Zhang, Y Shi, H Yin SIGIR 2022, 2022 | 27 | 2022 |
| Swarm intelligence in data science: applications, opportunities and challenges J Yang, L Qu, Y Shen, Y Shi, S Cheng, J Zhao, X Shen International Conference on Swarm Intelligence, 3-14, 2020 | 22 | 2020 |
| On-Device Recommender Systems: A Comprehensive Survey H Yin, L Qu, T Chen, W Yuan, R Zheng, J Long, X Xia, Y Shi, C Zhang arXiv preprint arXiv:2401.11441, 2024 | 15 | 2024 |
| HeteFedRec: Federated Recommender Systems with Model Heterogeneity W Yuan, L Qu, L Cui, Y Tong, X Zhou, H Yin ICDE 2024, 2023 | 12 | 2023 |
| When cooperative co-evolution meets coordinate descent: Theoretically deeper understandings and practically better implementations Q Duan, C Shao, L Qu, Y Shi, B Niu 2019 IEEE Congress on Evolutionary Computation (CEC), 721-730, 2019 | 10 | 2019 |
| Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation L Qu, W Yuan, R Zheng, L Cui, Y Shi, H Yin WWW 2024, 2024 | 6 | 2024 |
| Personalized Elastic Embedding Learning for On-Device Recommendation R Zheng, L Qu, T Chen, K Zheng, Y Shi, H Yin IEEE Transactions on Knowledge and Data Engineering, 2023 | 4 | 2023 |
| Robust federated contrastive recommender system against model poisoning attack W Yuan, C Yang, L Qu, G Ye, QVH Nguyen, H Yin arXiv preprint arXiv:2403.20107, 2024 | 3 | 2024 |
| Hide Your Model: A Parameter Transmission-free Federated Recommender System W Yuan, C Yang, L Qu, QVH Nguyen, J Li, H Yin ICDE 2024, 2023 | 3 | 2023 |
| Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation R Zheng, L Qu, T Chen, L Cui, Y Shi, H Yin WWW 2024, 2024 | 2 | 2024 |
| Poisoning Decentralized Collaborative Recommender System and Its Countermeasures R Zheng, L Qu, T Chen, K Zheng, Y Shi, H Yin arXiv preprint arXiv:2404.01177, 2024 | 1 | 2024 |
| Energy gaps of graphene clusters: the first-principles calculations based on high-throughput screening L Qu, Z Liu, X Yang Molecular Simulation 43 (7), 558-562, 2017 | 1 | 2017 |
| PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender System W Yuan, C Yang, L Qu, QVH Nguyen, G Ye, H Yin arXiv preprint arXiv:2406.05387, 2024 | | 2024 |
| Automated Similarity Metric Generation for Recommendation L Qu, Y Lin, W Yuan, X Wan, Y Shi, H Yin arXiv preprint arXiv:2404.11818, 2024 | | 2024 |
| On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm H Yin, T Chen, L Qu, B Cui WWW 2024, 2023 | | 2023 |
Hongzhi YinProfessor and ARC Future Fellow, University of Queensland在 uq.edu.au 的电子邮件经过验证
