| Sketchml: Accelerating distributed machine learning with data sketches J Jiang, F Fu, T Yang, B Cui Proceedings of the 2018 International Conference on Management of Data, 1269 …, 2018 | 105 | 2018 |
| VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning F Fu, Y Shao, L Yu, J Jiang, H Xue, Y Tao, B Cui Proceedings of the 2021 International Conference on Management of Data, 563-576, 2021 | 51 | 2021 |
| Don’t waste your bits! squeeze activations and gradients for deep neural networks via tinyscript F Fu, Y Hu, Y He, J Jiang, Y Shao, C Zhang, B Cui International Conference on Machine Learning, 3304-3314, 2020 | 46 | 2020 |
| Dimboost: Boosting gradient boosting decision tree to higher dimensions J Jiang, B Cui, C Zhang, F Fu Proceedings of the 2018 International Conference on Management of Data, 1363 …, 2018 | 44 | 2018 |
| An experimental evaluation of large scale GBDT systems F Fu, J Jiang, Y Shao, B Cui arXiv preprint arXiv:1907.01882, 2019 | 29 | 2019 |
| Blindfl: Vertical federated machine learning without peeking into your data F Fu, H Xue, Y Cheng, Y Tao, B Cui Proceedings of the 2022 International Conference on Management of Data, 1316 …, 2022 | 22 | 2022 |
| SKCompress: compressing sparse and nonuniform gradient in distributed machine learning J Jiang, F Fu, T Yang, Y Shao, B Cui The VLDB Journal 29 (5), 945-972, 2020 | 18 | 2020 |
| Towards communication-efficient vertical federated learning training via cache-enabled local updates F Fu, X Miao, J Jiang, H Xue, B Cui arXiv preprint arXiv:2207.14628, 2022 | 14 | 2022 |
| Kvsagg: Secure aggregation of distributed key-value sets Y Wu, S Dong, Y Zhou, Y Zhao, F Fu, T Yang, C Niu, F Wu, B Cui 2023 IEEE 39th International Conference on Data Engineering (ICDE). IEEE, 2023 | 4 | 2023 |
| Analyzing online transaction networks with network motifs J Jiang, Y Hu, X Li, W Ouyang, Z Wang, F Fu, B Cui Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 4 | 2022 |
| Osdp: Optimal sharded data parallel for distributed deep learning Y Jiang, F Fu, X Miao, X Nie, B Cui arXiv preprint arXiv:2305.09940, 2023 | 3 | 2023 |
| Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent X Nie, Y Liu, F Fu, J Xue, D Jiao, X Miao, Y Tao, B Cui arXiv preprint arXiv:2303.02868, 2023 | 3 | 2023 |
| Vf-ps: How to select important participants in vertical federated learning, efficiently and securely? J Jiang, L Burkhalter, F Fu, B Ding, B Du, A Hithnawi, B Li, C Zhang Advances in Neural Information Processing Systems 35, 2088-2101, 2022 | 3 | 2022 |
| Key technology and innovation of privacy preserving computing FU Fangcheng, HOU Chen, C Yong, TAO Yangyu Information and Communications Technology and Policy 47 (6), 27, 2021 | 3 | 2021 |
| PCG: a privacy preserving collaborative graph neural network training framework X Miao, W Zhang, Y Jiang, F Fu, Y Shao, L Chen, Y Tao, G Cao, B Cui The VLDB Journal 32 (4), 717-736, 2023 | 2 | 2023 |
| Training method and system for decision tree model, storage medium, and prediction method J Jiang, FU Fangcheng US Patent App. 17/163,343, 2021 | 1 | 2021 |
| Improving Automatic Parallel Training via Balanced Memory Workload Optimization Y Wang, Y Jiang, X Miao, F Fu, X Nie, B Cui arXiv preprint arXiv:2307.02031, 2023 | | 2023 |
| FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference Z Yu, H Li, F Fu, X Miao, B Cui arXiv preprint arXiv:2305.17423, 2023 | | 2023 |
| Data processing method and apparatus, device, and computer-readable storage medium FU Fangcheng, J Jiang, PAN Junwei, HOU Chen, XUE Huanran, ... US Patent App. 18/072,313, 2023 | | 2023 |
| Secure multi-party computation method and apparatus, device, and storage medium Y Cheng, TAO Yangyu, FU Fangcheng US Patent App. 17/992,685, 2023 | | 2023 |
Bin CUIProfessor of Computer Science, Peking UniversityVerified email at pku.edu.cn
