| Blogel: A block-centric framework for distributed computation on real-world graphs D Yan, J Cheng, Y Lu, W Ng Proceedings of the VLDB Endowment 7 (14), 1981-1992, 2014 | 313 | 2014 |
| Large-scale distributed graph computing systems: An experimental evaluation Y Lu, J Cheng, D Yan, H Wu Proceedings of the VLDB Endowment 8 (3), 281-292, 2014 | 227 | 2014 |
| Effective techniques for message reduction and load balancing in distributed graph computation D Yan, J Cheng, Y Lu, W Ng Proceedings of the 24th International Conference on World Wide Web, 1307-1317, 2015 | 158 | 2015 |
| Pregel algorithms for graph connectivity problems with performance guarantees D Yan, J Cheng, K Xing, Y Lu, W Ng, Y Bu Proceedings of the VLDB Endowment 7 (14), 1821-1832, 2014 | 147 | 2014 |
| G-miner: an efficient task-oriented graph mining system H Chen, M Liu, Y Zhao, X Yan, D Yan, J Cheng Proceedings of the Thirteenth EuroSys Conference, 1-12, 2018 | 142 | 2018 |
| Core decomposition in large temporal graphs H Wu, J Cheng, Y Lu, Y Ke, Y Huang, D Yan, H Wu 2015 IEEE international conference on big data (Big data), 649-658, 2015 | 133 | 2015 |
| Big graph analytics platforms D Yan, Y Bu, Y Tian, A Deshpande Foundations and Trends in Databases 7 (1-2), 1-195, 2017 | 119 | 2017 |
| Diversified temporal subgraph pattern mining Y Yang, D Yan, H Wu, J Cheng, S Zhou, JCS Lui Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 89 | 2016 |
| Fast federated machine unlearning with nonlinear functional theory T Che, Y Zhou, Z Zhang, L Lyu, J Liu, D Yan, D Dou, J Huan International conference on machine learning, 4241-4268, 2023 | 81 | 2023 |
| Mining probabilistically frequent sequential patterns in large uncertain databases Z Zhao, D Yan, W Ng IEEE transactions on knowledge and data engineering 26 (5), 1171-1184, 2013 | 73 | 2013 |
| Efficient algorithms for finding optimal meeting point on road networks D Yan, Z Zhao, W Ng Proceedings of the VLDB Endowment 4 (11), 968-979, 2011 | 72 | 2011 |
| G-thinker: A distributed framework for mining subgraphs in a big graph D Yan, G Guo, MMR Chowdhury, MT Özsu, WS Ku, JCS Lui 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1369-1380, 2020 | 62 | 2020 |
| Quegel: A general-purpose query-centric framework for querying big graphs D Yan, J Cheng, MT Özsu, F Yang, Y Lu, J Lui, Q Zhang, W Ng arXiv preprint arXiv:1601.06497, 2016 | 62 | 2016 |
| Trajnet: A trajectory-based deep learning model for traffic prediction B Hui, D Yan, H Chen, WS Ku Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 57 | 2021 |
| Graphd: Distributed vertex-centric graph processing beyond the memory limit D Yan, Y Huang, M Liu, H Chen, J Cheng, H Wu, C Zhang IEEE Transactions on Parallel and Distributed Systems 29 (1), 99-114, 2017 | 46 | 2017 |
| Forecasting stock prices using stock correlation graph: A graph convolutional network approach X Yin, D Yan, A Almudaifer, S Yan, Y Zhou 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 42 | 2021 |
| Fraction-score: A new support measure for co-location pattern mining HKH Chan, C Long, D Yan, RCW Wong 2019 IEEE 35th international conference on data engineering (ICDE), 1514-1525, 2019 | 42 | 2019 |
| Mining probabilistically frequent sequential patterns in uncertain databases Z Zhao, D Yan, W Ng Proceedings of the 15th international conference on extending database …, 2012 | 42 | 2012 |
| Efficient methods for finding influential locations with adaptive grids D Yan, RCW Wong, W Ng Proceedings of the 20th ACM international conference on Information and …, 2011 | 41 | 2011 |
| Structure prediction and materials design with generative neural networks D Yan, AD Smith, CC Chen Nature Computational Science 3 (7), 572-574, 2023 | 39 | 2023 |
Wilfred NgProfessor of Computer Science and Engineering, Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
