CASA: Clustered Federated Learning with Asynchronous Clients

Author:

Liu Boyi1ORCID,Ma Yiming1ORCID,Zhou Zimu2ORCID,Shi Yexuan1ORCID,Li Shuyuan1ORCID,Tong Yongxin1ORCID

Affiliation:

1. SKLCCSE Lab, Beihang University, Beijing, China

2. School of Data Science, City University of Hong Kong, Hong Kong, China

Funder

CityU APRC grant

Beihang University Basic Research

Didi Collaborative Research Program

National Science Foundation of China (NSFC)

Beijing Natural Science Foundation

Publisher

ACM

Reference49 articles.

1. Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better

2. Federated learning with hierarchical clustering of local updates to improve training on non-IID data

3. Sebastian Caldas, Sai Meher Karthik Duddu, Peter Wu, Tian Li, Jakub Konevcnỳ, H Brendan McMahan, Virginia Smith, and Ameet Talwalkar. 2018. Leaf: A benchmark for federated settings. arXiv preprint arXiv:1812.01097 (2018).

4. pFL-bench: A comprehensive benchmark for personalized federated learning;Chen Daoyuan;Advances in Neural Information Processing Systems,2022

5. Ming Chen, Bingcheng Mao, and Tianyi Ma. 2019. Efficient and robust asynchronous federated learning with stragglers. In Proceedings of ICLR.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3