Fangcheng Fu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 30

Top Topics

Gradient Boosting

Adobe Photoshop

Limited Resources

Machine Learning

Top Venues

SIGMOD Conference

Proc. VLDB Endow.

Publications

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 (2024)
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 (2024)
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 (2024)
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference. AAAI (2024)
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)
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) (2024)
Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui
CG: a privacy preserving collaborative graph neural network training framework. VLDB J. 32 (4) (2023)
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 (2023)
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) (2023)
Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui
Improving Automatic Parallel Training via Balanced Memory Workload Optimization. CoRR (2023)
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 (2023)
Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. CoRR (2023)
Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. IJCAI (2023)
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)
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference. CoRR (2023)
Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. CoRR (2022)
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)
Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data. CoRR (2022)
Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui
Analyzing Online Transaction Networks with Network Motifs. KDD (2022)
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) (2022)
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)
Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data. SIGMOD Conference (2022)
Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui
Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. SIGMOD Conference (2021)
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 (2021)
Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui
SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. VLDB J. 29 (5) (2020)
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)
Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui
An Experimental Evaluation of Large Scale GBDT Systems. CoRR (2019)
Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui
An Experimental Evaluation of Large Scale GBDT Systems. Proc. VLDB Endow. 12 (11) (2019)
Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui
SketchML: Accelerating Distributed Machine Learning with Data Sketches. SIGMOD Conference (2018)
Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu
DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. SIGMOD Conference (2018)