| Simgnn: A neural network approach to fast graph similarity computation Y Bai, H Ding, S Bian, T Chen, Y Sun, W Wang Proceedings of the twelfth ACM international conference on web search and …, 2019 | 343 | 2019 |
| Are powerful graph neural nets necessary? a dissection on graph classification T Chen, S Bian, Y Sun arXiv preprint arXiv:1905.04579, 2019 | 80 | 2019 |
| Efficient algorithms for budgeted influence maximization on massive social networks S Bian, Q Guo, S Wang, JX Yu Proceedings of the VLDB Endowment 13 (9), 1498-1510, 2020 | 45 | 2020 |
| Dataprep. eda: Task-centric exploratory data analysis for statistical modeling in python J Peng, W Wu, B Lockhart, S Bian, JN Yan, L Xu, Z Chi, JM Rzeszotarski, ... Proceedings of the 2021 International Conference on Management of Data, 2271 …, 2021 | 38 | 2021 |
| Finding top-r influential communities under aggregation functions Y Peng, S Bian, R Li, S Wang, JX Yu 2022 IEEE 38th International Conference on Data Engineering (ICDE), 1941-1954, 2022 | 10 | 2022 |
| CrowdTC: Crowd-powered learning for text classification K Yang, Y Gao, L Liang, S Bian, L Chen, B Zheng ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (1), 1-23, 2021 | 8 | 2021 |
| Certifiable Robustness for Naive Bayes Classifiers S Bian, X Ouyang, Z Fan, P Koutris arXiv preprint arXiv:2303.04811, 2023 | 2 | 2023 |
| Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native Y Lu, S Bian, L Chen, Y He, Y Hui, M Lentz, B Li, F Liu, J Li, Q Liu, R Liu, ... arXiv preprint arXiv:2401.12230, 2024 | 1 | 2024 |
| Does compressing activations help model parallel training? S Bian, D Li, H Wang, EP Xing, S Venkataraman arXiv preprint arXiv:2301.02654, 2023 | 1 | 2023 |
