FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction-Reference-Cited by-同舟云学术

FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
Short-container-title:

Author:

Gao Liang¹,Fu Huazhu²,Li Li³,Chen Yingwen¹,Xu Ming¹,Xu Cheng-Zhong³

Affiliation:

1. National University of Defense Technology,China

2. IHPC, ASTAR,Singapore

3. University of Macau,IOTSC,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878652.pdf?arnumber=9878652

Reference31 articles.

1. Federated reinforcement learning;zhuo;CoRR abs/1901 08277,2019

2. Federated learning with non-iid data;zhao;ArXiv Preprint,2018

3. Konstantin Mishchenko, and Peter. Tighter theory for local sgd on identical and heterogeneous data;khaled;International Conference on Artificial Intelligence and Statistics,2020

4. Federated Optimization: Distributed Ma-chine Learning for On-Device Intelligence;konecny;ArXiv e-prints,2016

Cited by 120 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FedCCL: Federated dual-clustered feature contrast under domain heterogeneity;Information Fusion;2025-01

2. Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading;Computational and Structural Biotechnology Journal;2024-12

3. Learning by imitating the classics: Mitigating class imbalance in federated learning via simulated centralized learning;Expert Systems with Applications;2024-12

4. CESA: Communication efficient secure aggregation scheme via sparse graph in federated learning;Journal of Network and Computer Applications;2024-11

5. Generative data augmentation with differential privacy for non-IID problem in decentralized clinical machine learning;Future Generation Computer Systems;2024-11