| Labeling trick: A theory of using graph neural networks for multi-node representation learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems 34, 9061-9073, 2021 | 204 | 2021 |
| GraphBIG: understanding graph computing in the context of industrial solutions L Nai, Y Xia, IG Tanase, H Kim, CY Lin Proceedings of the International Conference for High Performance Computing …, 2015 | 198 | 2015 |
| Decoupling the depth and scope of graph neural networks H Zeng, M Zhang, Y Xia, A Srivastava, A Malevich, R Kannan, V Prasanna, ... Advances in Neural Information Processing Systems 34, 19665-19679, 2021 | 194 | 2021 |
| LDBC Graphalytics: A benchmark for large-scale graph analysis on parallel and distributed platforms A Iosup, T Hegeman, WL Ngai, S Heldens, A Prat-Pérez, T Manhardto, ... Proceedings of the VLDB Endowment 9 (13), 1317-1328, 2016 | 161 | 2016 |
| Adaptive sampling schemes for clustering streaming graphs KL Wu, Y Xia US Patent 9,886,521, 2018 | 132 | 2018 |
| Insider threat prediction AR Coden, CY Lin, WY Lin, Y Xia US Patent 9,589,245, 2017 | 97 | 2017 |
| Llm-rec: Personalized recommendation via prompting large language models H Lyu, S Jiang, H Zeng, Y Xia, Q Wang, S Zhang, R Chen, C Leung, ... arXiv preprint arXiv:2307.15780, 2023 | 76 | 2023 |
| Revisiting graph neural networks for link prediction M Zhang, P Li, Y Xia, K Wang, L Jin | 75 | 2020 |
| Topologically adaptive parallel breadth-first search on multicore processors Y Xia, VK Prasanna Proc. 21st Int’l. Conf. on Parallel and Distributed Computing Systems (PDCS’09), 2009 | 71 | 2009 |
| Explainable fairness in recommendation Y Ge, J Tan, Y Zhu, Y Xia, J Luo, S Liu, Z Fu, S Geng, Z Li, Y Zhang Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 70 | 2022 |
| Rawlsgcn: Towards rawlsian difference principle on graph convolutional network J Kang, Y Zhu, Y Xia, J Luo, H Tong Proceedings of the ACM Web Conference 2022, 1214-1225, 2022 | 60 | 2022 |
| Joint knowledge graph completion and question answering L Liu, B Du, J Xu, Y Xia, H Tong Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 52 | 2022 |
| Scalable spectral clustering using random binning features L Wu, PY Chen, IEH Yen, F Xu, Y Xia, C Aggarwal Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 47 | 2018 |
| Balancing consistency and disparity in network alignment S Zhang, H Tong, L Jin, Y Xia, Y Guo Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 46 | 2021 |
| Scalable global alignment graph kernel using random features: From node embedding to graph embedding L Wu, IEH Yen, Z Zhang, K Xu, L Zhao, X Peng, Y Xia, C Aggarwal Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 40 | 2019 |
| Thermal face image use for health estimation JH Lai, Y Xia, JH Hsiao, Y Zhang US Patent App. 15/870,617, 2019 | 36 | 2019 |
| Sparkbench–a spark performance testing suite D Agrawal, A Butt, K Doshi, JL Larriba-Pey, M Li, FR Reiss, F Raab, ... Performance Evaluation and Benchmarking: Traditional to Big Data to Internet …, 2016 | 35 | 2016 |
| Graph analytics and storage Y Xia, IG Tanase, L Nai, W Tan, Y Liu, J Crawford, CY Lin 2014 IEEE International Conference on Big Data (Big Data), 942-951, 2014 | 35 | 2014 |
| A message-passing multi-softcore architecture on FPGA for breadth-first search Q Wang, W Jiang, Y Xia, V Prasanna 2010 International Conference on Field-Programmable Technology, 70-77, 2010 | 34 | 2010 |
| Finding the best k in core decomposition: A time and space optimal solution D Chu, F Zhang, X Lin, W Zhang, Y Zhang, Y Xia, C Zhang 2020 IEEE 36th International Conference on Data Engineering (ICDE), 685-696, 2020 | 31 | 2020 |
