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 | 118 | 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 | 77 | 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 | 55 | 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 | 45 | 2018 |
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 | 41 | 2022 |
An experimental evaluation of large scale GBDT systems F Fu, J Jiang, Y Shao, B Cui arXiv preprint arXiv:1907.01882, 2019 | 34 | 2019 |
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 | 21 | 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 | 20 | 2020 |
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 | 11 | 2022 |
Osdp: Optimal sharded data parallel for distributed deep learning Y Jiang, F Fu, X Miao, X Nie, B Cui arXiv preprint arXiv:2209.13258, 2022 | 6 | 2022 |
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 | 6 | 2022 |
Retrieval-Augmented Generation for AI-Generated Content: A Survey P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu, L Yang, W Zhang, B Cui arXiv preprint arXiv:2402.19473, 2024 | 5 | 2024 |
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 | 5 | 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 | 5 | 2023 |
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), 1775-1789, 2023 | 4 | 2023 |
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 |
Fisedit: Accelerating text-to-image editing via cache-enabled sparse diffusion inference Z Yu, H Li, F Fu, X Miao, B Cui arXiv e-prints, arXiv: 2305.17423, 2023 | 2 | 2023 |
Vertical federated logistic regression via homomorphic encryption and secret sharing FU Fangcheng, LIU Shu, C Yong, TAO Yangyu Information and Communications Technology and Policy 48 (5), 34, 2022 | 2 | 2022 |
Training method and system for decision tree model, storage medium, and prediction method J Jiang, FU Fangcheng US Patent App. 17/163,343, 2021 | 2 | 2021 |
Improving Automatic Parallel Training via Balanced Memory Workload Optimization Y Wang, Y Jiang, X Miao, F Fu, S Zhu, X Nie, Y Tu, B Cui IEEE Transactions on Knowledge and Data Engineering, 2024 | 1 | 2024 |