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Fangcheng Fu
Fangcheng Fu
Verified email at pku.edu.cn
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Year
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
1162018
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
702021
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
532020
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
452018
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
332022
An experimental evaluation of large scale GBDT systems
F Fu, J Jiang, Y Shao, B Cui
arXiv preprint arXiv:1907.01882, 2019
322019
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
202020
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
192022
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
112022
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
62022
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
62022
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
52023
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
42023
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
42023
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
32021
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
22023
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
22022
Training method and system for decision tree model, storage medium, and prediction method
J Jiang, FU Fangcheng
US Patent App. 17/163,343, 2021
22021
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
12024
K-core decomposition on super large graphs with limited resources
S Gao, J Xu, X Li, F Fu, W Zhang, W Ouyang, Y Tao, B Cui
Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, 413-422, 2022
12022
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