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Fangcheng Fu
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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
1312024
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
1312018
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
1002021
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
772020
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
522022
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
492018
An experimental evaluation of large scale GBDT systems
F Fu, J Jiang, Y Shao, B Cui
arXiv preprint arXiv:1907.01882, 2019
342019
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
252022
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
252022
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
222020
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
132023
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
122022
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
112022
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
92023
Pqcache: Product quantization-based kvcache for long context llm inference
H Zhang, X Ji, Y Chen, F Fu, X Miao, X Nie, W Chen, B Cui
arXiv preprint arXiv:2407.12820, 2024
82024
Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference
Z Yu, H Li, F Fu, X Miao, B Cui
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16605 …, 2024
82024
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
82024
Generative and contrastive paradigms are complementary for graph self-supervised learning
Y Wang, X Yan, C Hu, Q Xu, C Yang, F Fu, W Zhang, H Wang, B Du, ...
2024 IEEE 40th International Conference on Data Engineering (ICDE), 3364-3378, 2024
52024
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
52023
Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs
P Zhao, H Zhang, F Fu, X Nie, Q Liu, F Yang, Y Peng, D Jiao, S Li, J Xue, ...
arXiv preprint arXiv:2407.12117, 2024
32024
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