| Secureboost: A lossless federated learning framework K Cheng, T Fan, Y Jin, Y Liu, T Chen, D Papadopoulos, Q Yang IEEE Intelligent Systems 36 (6), 87-98, 2021 | 709 | 2021 |
| Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective Y Jin, X Wei, Y Liu, Q Yang arXiv preprint arXiv:2002.11545, 2020 | 94* | 2020 |
| Dane: Domain adaptive network embedding Y Zhang, G Song, L Du, S Yang, Y Jin Proceedings of the Twenty-Eighth International Conference on International …, 2019 | 79 | 2019 |
| Graph Structural-topic Neural Network Q Long*, Y Jin*, G Song, Y Li, W Lin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 56 | 2020 |
| GraLSP: Graph Neural Networks with Local Structural Patterns. Y Jin, G Song, C Shi The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 4361-4368, 2020 | 54 | 2020 |
| Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting Y Jin, K Chen, Q Yang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 36 | 2022 |
| Hierarchical Community Structure Preserving Network Embedding: A Subspace Approach Q Long, Y Wang, L Du, G Song, Y Jin, W Lin Proceedings of the 28th ACM International Conference on Information and …, 2019 | 36 | 2019 |
| Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels Q Long*, Y Jin*, Y Wu*, G Song Proceedings of the Web Conference 2021, 1204-1214, 2021 | 32 | 2021 |
| Domain Adaptive Classification on Heterogeneous Information Networks. S Yang, G Song, Y Jin, L Du IJCAI, 1410-1416, 2020 | 28 | 2020 |
| GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks Y Li, Y Jin, G Song, Z Zhu, C Shi, Y Wang Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4206-4214, 2021 | 27 | 2021 |
| Scalable and Efficient Full-Graph GNN Training for Large Graphs X Wan, K Xu, X Liao, Y Jin, K Chen, X Jin Proceedings of the ACM on Management of Data 1 (2), 1-23, 2023 | 26 | 2023 |
| A Survey on Vertical Federated Learning: From a Layered Perspective L Yang, D Chai, J Zhang, Y Jin, L Wang, H Liu, H Tian, Q Xu, K Chen arXiv preprint arXiv:2304.01829, 2023 | 24 | 2023 |
| Federated Learning without Full Labels: A Survey Y Jin, Y Liu, K Chen, Q Yang IEEE Data Engineering Bulletin 46 (1), 27-51, 2023 | 17 | 2023 |
| Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities Y Jin, K Chen, Q Yang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 16 | 2023 |
| Data Resampling for Federated Learning with Non-IID Labels Z Tang, Z Hu, S Shi, Y Cheung, Y Jin, Z Ren, X Chu IJCAI International Workshop on Federated and Transfer Learning (FTL-IJCAI'21), 2021 | 16 | 2021 |
| Secure Forward Aggregation for Vertical Federated Neural Networks S Cai, D Chai, L Yang, J Zhang, Y Jin, L Wang, K Guo, K Chen IJCAI International Workshop on Trustworthy Federated Learning (FL-IJCAI'22), 2022 | 11 | 2022 |
| EPNE: Evolutionary Pattern Preserving Network Embedding J Wang*, Y Jin*, G Song, X Ma Proceedings of the 24th European Conference on Artificial Intelligence, 1603 …, 2020 | 8 | 2020 |
| Ternary Hashing C Liu, L Fan, KW Ng, Y Jin, C Ju, T Zhang, CS Chan, Q Yang arXiv preprint arXiv:2103.09173, 2021 | 6 | 2021 |
| Deep convolutional neural network based medical concept normalization G Song, Q Long, Y Luo, Y Wang, Y Jin IEEE Transactions on Big Data 8 (5), 1195-1208, 2020 | 6 | 2020 |
| Active Domain Transfer on Network Embedding L Jin, Y Zhang, G Song, Y Jin Proceedings of The Web Conference 2020, 2683-2689, 2020 | 4 | 2020 |
Qiang Yang (杨强）Chief AI Officer@WeBank, Prof. Emeritus @HKUST, IJCAI President 2017-19, AAAI-21 General ChairVerified email at cse.ust.hk
