Modeling global distribution for federated learning with label distribution skew-Reference-Cited by-同舟云学术

Modeling global distribution for federated learning with label distribution skew

Published:2023-11 Issue: Volume:143 Page:109724
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Sheng Tao,Shen Chengchao^ORCID,Liu Yuan,Ou Yeyu,Qu Zhe,Liang Yixiong^ORCID,Wang Jianxin

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference49 articles.

1. Lcu-net: a novel low-cost u-net for environmental microorganism image segmentation;Zhang;Pattern Recognit.,2021

2. A comprehensive survey with quantitative comparison of image analysis methods for microorganism biovolume measurements;Zhang;Arch. Comput. Methods Eng.,2022

3. Communication-efficient learning of deep networks from decentralized data;McMahan,2017

4. Advances and open problems in federated learning;Peter;Found. Trend. Mach. Learn.,2021

5. Federated optimization in heterogeneous networks;Li,2020

Cited by 5 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. Federated zero-shot learning with mid-level semantic knowledge transfer;Pattern Recognition;2024-12

2. GANFAT: Robust federated adversarial learning with label distribution skew;Future Generation Computer Systems;2024-11

3. FedCPD: Addressing label distribution skew in federated learning with class proxy decoupling and proxy regularization;Information Fusion;2024-10

4. Exploring Federated Learning Tendencies Using a Semantic Keyword Clustering Approach;Information;2024-06-28

5. Personalized federated adaptive regularization for heterogeneous medical image classification: COVID-19 CT results;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05