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ORCIDFangcheng Fu
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2020 – today
- 2024
[j6]Fangcheng Fu
, Xuanyu Wang, Jiawei Jiang, Huanran Xue, Bui Cui:
ProjPert: Projection-Based Perturbation for Label Protection in Split Learning Based Vertical Federated Learning. IEEE Trans. Knowl. Data Eng. 36(7): 3417-3428 (2024)- [c13]Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui:
Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference. AAAI 2024: 16605-16613 - [c12]Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang:
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. ICDE 2024: 3364-3378 - [c11]Xupeng Miao, Shenhan Zhu, Fangcheng Fu, Ziyu Guo, Zhi Yang, Yaofeng Tu, Zhihao Jia, Bin Cui:
X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling. IJCAI 2024: 8179-8187 - [i13]Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Bin Cui:
Retrieval-Augmented Generation for AI-Generated Content: A Survey. CoRR abs/2402.19473 (2024) - [i12]Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui:
Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs. CoRR abs/2407.12117 (2024) - [i11]Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui:
PQCache: Product Quantization-based KVCache for Long Context LLM Inference. CoRR abs/2407.12820 (2024) - [i10]Yujie Wang, Shenhan Zhu, Fangcheng Fu, Xupeng Miao, Jie Zhang, Juan Zhu, Fan Hong, Yong Li, Bin Cui:
Efficient Multi-Task Large Model Training via Data Heterogeneity-aware Model Management. CoRR abs/2409.03365 (2024) - [i9]Qiang Huang, Xiao Yan, Xin Wang, Susie Xi Rao, Zhichao Han, Fangcheng Fu, Wentao Zhang, Jiawei Jiang:
Retrofitting Temporal Graph Neural Networks with Transformer. CoRR abs/2409.05477 (2024) - 2023
- [j5]Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui:
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent. Proc. VLDB Endow. 16(12): 3781-3794 (2023) - [j4]Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui:
P2CG: a privacy preserving collaborative graph neural network training framework. VLDB J. 32(4): 717-736 (2023) - [c10]Yuhan Wu, Siyuan Dong, Yi Zhou, Yikai Zhao, Fangcheng Fu, Tong Yang, Chaoyue Niu, Fan Wu, Bin Cui:
KVSAgg: Secure Aggregation of Distributed Key-Value Sets. ICDE 2023: 1775-1789 - [c9]Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui:
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. IJCAI 2023: 2142-2150 - [i8]Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui:
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent. CoRR abs/2303.02868 (2023) - [i7]Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui:
FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference. CoRR abs/2305.17423 (2023) - [i6]Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui:
Improving Automatic Parallel Training via Balanced Memory Workload Optimization. CoRR abs/2307.02031 (2023) - [i5]Yuxiang Wang, Xiao Yan, Chuang Hu, Fangcheng Fu, Wentao Zhang, Hao Wang, Shuo Shang, Jiawei Jiang:
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. CoRR abs/2310.15523 (2023) - 2022
- [j3]Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui:
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. Proc. VLDB Endow. 15(10): 2111-2120 (2022) - [c8]Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui:
Analyzing Online Transaction Networks with Network Motifs. KDD 2022: 3098-3106 - [c7]Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang:
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS 2022 - [c6]Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui:
K-core decomposition on super large graphs with limited resources. SAC 2022: 413-422 - [c5]Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui:
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data. SIGMOD Conference 2022: 1316-1330 - [i4]Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui:
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data. CoRR abs/2206.07975 (2022) - [i3]Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui:
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. CoRR abs/2207.14628 (2022) - 2021
- [c4]Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui:
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. SIGMOD Conference 2021: 563-576 - [i2]Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui:
K-Core Decomposition on Super Large Graphs with Limited Resources. CoRR abs/2112.14840 (2021) - 2020
- [j2]Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui:
SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. VLDB J. 29(5): 945-972 (2020) - [c3]Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui:
Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. ICML 2020: 3304-3314
2010 – 2019
- 2019
- [j1]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. Proc. VLDB Endow. 12(11): 1357-1370 (2019) - [i1]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. CoRR abs/1907.01882 (2019) - 2018
- [c2]Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui:
SketchML: Accelerating Distributed Machine Learning with Data Sketches. SIGMOD Conference 2018: 1269-1284 - [c1]Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu:
DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. SIGMOD Conference 2018: 1363-1376
Coauthor Index
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