| A survey on federated learning systems: vision, hype and reality for data privacy and protection Q Li, Z Wen, Z Wu, S Hu, N Wang, Y Li, X Liu, B He IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019 | 464 | 2019 |
| ThunderSVM: A fast SVM library on GPUs and CPUs Z Wen, J Shi, Q Li, B He, J Chen Journal of Machine Learning Research (JMLR) 19, 797-801, 2018 | 177 | 2018 |
| Practical Federated Gradient Boosting Decision Trees Q Li, Z Wen, B He AAAI Conference on Artificial Intelligence (AAAI), 2020 | 130 | 2020 |
| Top- Most Influential Location Selection J Huang, Z Wen, J Qi, R Zhang, J Chen, Z He ACM International Conference on Information and Knowledge Management (CIKM), 2011 | 69 | 2011 |
| Privacy-Preserving Gradient Boosting Decision Trees Q Li, Z Wu, Z Wen, B He AAAI Conference on Artificial Intelligence (AAAI), 2020 | 50 | 2020 |
| Efficient Gradient Boosted Decision Tree Training on GPUs Z Wen, B He, K Ramamohanarao, S Lu, J Shi International Parallel and Distributed Processing Symposium (IPDPS), 234-243, 2018 | 43 | 2018 |
| Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training Z Wen, J Shi, B He, J Chen, K Ramamohanarao, Q Li IEEE Transactions on Parallel and Distributed Systems (TPDS), 2019 | 35 | 2019 |
| The safest path via safe zones S Aljubayrin, J Qi, CS Jensen, R Zhang, Z He, Z Wen 2015 IEEE 31st International Conference on Data Engineering (ICDE), 531-542, 2015 | 32 | 2015 |
| Indexable online time series segmentation with error bound guarantee J Qi, R Zhang, K Ramamohanarao, H Wang, Z Wen, D Wu World Wide Web 18, 359-401, 2015 | 26 | 2015 |
| MASCOT: Fast and Highly Scalable SVM Cross-validation using GPUs and SSDs Z Wen, R Zhang, K Ramamohanarao, J Qi, K Taylor IEEE International Conference on Data Mining (ICDM), 580-589, 2014 | 22 | 2014 |
| Improving Efficiency of SVM -Fold Cross-Validation by Alpha Seeding. Z Wen, B Li, K Ramamohanarao, J Chen, Y Chen, R Zhang AAAI Conference on Artificial Intelligence (AAAI), 2768-2774, 2017 | 20 | 2017 |
| ThunderGBM: Fast GBDTs and Random Forests on GPUs Z Wen, H Liu, J Shi, B He, Q Li, J Chen Journal of Machine Learning Research (JMLR) 21 (108), 2020 | 19 | 2020 |
| A Survey on Federated Learning Systems: Vision Q Li, Z Wen, Z Wu, S Hu, N Wang, B He Hype and Reality for Data Privacy and Protection, 2019 | 19 | 2019 |
| Efficient subgraph matching using gpus X Lin, R Zhang, Z Wen, H Wang, J Qi Databases Theory and Applications: 25th Australasian Database Conference …, 2014 | 18 | 2014 |
| An Efficient Method for Min-dist Location Selection J Qi, Z Xu, Y Xue, Z Wen Australasian Database Conference, 2012 | 14* | 2012 |
| Adaptive kernel value caching for SVM training Q Li, Z Wen, B He IEEE transactions on neural networks and learning systems 31 (7), 2376-2386, 2019 | 13 | 2019 |
| Efficient Multi-Class Probabilistic SVMs on GPUs Z Wen, J Shi, B He, J Chen, Y Chen IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018 | 11 | 2018 |
| Analysis and evaluation of the top- most influential location selection query J Chen, J Huang, Z Wen, Z He, K Taylor, R Zhang Knowledge and Information Systems (KAIS) 43 (1), 181-217, 2015 | 11 | 2015 |
| Scalable and fast SVM regression using modern hardware Z Wen, R Zhang, K Ramamohanarao, L Yang World Wide Web 21, 261-287, 2018 | 10 | 2018 |
| RTSI: An Index Structure for Multi-Modal Real-Time Search on Live Audio Streaming Services Z Wen, X Liu, H Cao, B He IEEE International Conference on Data Engineering (ICDE), 1495-1506, 2018 | 10 | 2018 |
Bingsheng He, 何丙胜Professor, Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
