PECO: Probabilistic Evaluation-Based Client Selection for Federated Learning with Overlapping Clients

  • Allen Yang
  • , Shiyue Hou
  • , Yiming Xie
  • , Bo Sheng
  • , Ningfang Mi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings - 2025 27th IEEE International Conference on High Performance Computing and Communications, 11th IEEE International Conference on Data Science and Systems, 23rd IEEE International Conference on Smart City, 11th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications and 21st IEEE International Conference on Embedded Software and Systems, HPCC/DSS/SmartCity/DependSys/ICESS 2025
EditorsJia Hu, Geyong Min, Haozhe Wang, Wang Miao, Lexi Xu, Nektarios Georgalas, Zhiwei Zhao, Rui Jin, Guangyao Pang, Wei Han, Fei Hao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages750-757
Number of pages8
ISBN (Electronic)9798331568740
DOIs
StatePublished - 2025
Event27th IEEE International Conference on High Performance Computing and Communications, HPCC 2025 - Exeter, United Kingdom
Duration: Aug 13 2025Aug 15 2025

Publication series

NameProceedings - 2025 27th IEEE International Conference on High Performance Computing and Communications, 11th IEEE International Conference on Data Science and Systems, 23rd IEEE International Conference on Smart City, 11th IEEE International Conference on Dependability in Sensor, Cloud, and Big Data Systems and Applications and 21st IEEE International Conference on Embedded Software and Systems, HPCC/DSS/SmartCity/DependSys/ICESS 2025

Conference

Conference27th IEEE International Conference on High Performance Computing and Communications, HPCC 2025
Country/TerritoryUnited Kingdom
CityExeter
Period8/13/258/15/25

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management

Keywords

  • client selection
  • federated learning
  • non-iid data
  • overlapping data

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