Fangcheng Fu

According to our database, Fangcheng Fu authored at least 31 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ProjPert: Projection-Based Perturbation for Label Protection in Split Learning Based Vertical Federated Learning.

Fangcheng Fu, Xuanyu Wang, Jiawei Jiang, Huanran Xue, Bin Cui

IEEE Trans. Knowl. Data Eng., July, 2024

Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization.

Haoyang Li, Fangcheng Fu, Hao Ge, Sheng Lin, Xuanyu Wang, Jiawen Niu, Yujie Wang, Hailin Zhang, Xiaonan Nie, Bin Cui

CoRR, 2024

Gradual Learning: Optimizing Fine-Tuning with Partially Mastered Knowledge in Large Language Models.

Bozhou Li, Hao Liang, Yang Li, Fangcheng Fu, Hongzhi Yin, Conghui He, Wentao Zhang

CoRR, 2024

Retrofitting Temporal Graph Neural Networks with Transformer.

Qiang Huang, Xiao Yan, Xin Wang, Susie Xi Rao, Zhichao Han, Fangcheng Fu, Wentao Zhang, Jiawei Jiang

CoRR, 2024

Efficient Multi-Task Large Model Training via Data Heterogeneity-aware Model Management.

Yujie Wang, Shenhan Zhu, Fangcheng Fu, Xupeng Miao, Jie Zhang, Juan Zhu, Fan Hong, Yong Li, Bin Cui

CoRR, 2024

PQCache: Product Quantization-based KVCache for Long Context LLM Inference.

Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui

CoRR, 2024

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs.

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

CoRR, 2024

Retrieval-Augmented Generation for AI-Generated Content: A Survey.

Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, Bin Cui

CoRR, 2024

Enabling Parallelism Hot Switching for Efficient Training of Large Language Models.

Hao Ge, Fangcheng Fu, Haoyang Li, Xuanyu Wang, Sheng Lin, Yujie Wang, Xiaonan Nie, Hailin Zhang, Xupeng Miao, Bin Cui

Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles, 2024

X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling.

Xupeng Miao, Shenhan Zhu, Fangcheng Fu, Ziyu Guo, Zhi Yang, Yaofeng Tu, Zhihao Jia, Bin Cui

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.

Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference.

Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

P²CG: a privacy preserving collaborative graph neural network training framework.

Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui

VLDB J., July, 2023

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent.

Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui

Proc. VLDB Endow., 2023

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.

Yuxiang Wang, Xiao Yan, Chuang Hu, Fangcheng Fu, Wentao Zhang, Hao Wang, Shuo Shang, Jiawei Jiang

CoRR, 2023

Improving Automatic Parallel Training via Balanced Memory Workload Optimization.

Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui

CoRR, 2023

FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference.

Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui

CoRR, 2023

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.

Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

KVSAgg: Secure Aggregation of Distributed Key-Value Sets.

Yuhan Wu, Siyuan Dong, Yi Zhou, Yikai Zhao, Fangcheng Fu, Tong Yang, Chaoyue Niu, Fan Wu, Bin Cui

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update.

Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui

Proc. VLDB Endow., 2022

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates.

Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui

CoRR, 2022

BlindFL: Vertical Federated Machine Learning without Peeking into Your Data.

Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, Bin Cui

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

K-core decomposition on super large graphs with limited resources.

Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao, Bin Cui

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?

Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Analyzing Online Transaction Networks with Network Motifs.

Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

VF²Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning.

Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

SKCompress: compressing sparse and nonuniform gradient in distributed machine learning.

Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui

VLDB J., 2020

Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript.

Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

An Experimental Evaluation of Large Scale GBDT Systems.

Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui

Proc. VLDB Endow., 2019

2018

SketchML: Accelerating Distributed Machine Learning with Data Sketches.

Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui

Proceedings of the 2018 International Conference on Management of Data, 2018

DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions.

Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu

Proceedings of the 2018 International Conference on Management of Data, 2018