AMFL: Asynchronous Multi-level Federated Learning with Client Selection

Xuerui Li; Yangming Zhao; Chunming Qiao

doi:10.1109/iccc62479.2024.10681873

ScienceGate Book Chapters

JOURNAL ARTICLE

AMFL: Asynchronous Multi-level Federated Learning with Client Selection

Xuerui Li Yangming Zhao Chunming Qiao

Year: 2024 Pages: 1-6

DOI: 10.1109/iccc62479.2024.10681873

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Asynchronous communication Selection (genetic algorithm) Asynchronous learning Federated learning Artificial intelligence Computer network Synchronous learning

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.15

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Cryptography and Data Security

Physical Sciences → Computer Science → Artificial Intelligence

Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

Cooperative Communication and Network Coding

Physical Sciences → Computer Science → Computer Networks and Communications

AMFL: Asynchronous Multi-level Federated Learning with Client Selection

Metrics

Topics

Related Documents

Asynchronous Wireless Federated Learning With Probabilistic Client Selection

Client Selection for Asynchronous Federated Learning with Fairness Consideration

Client Selection With Staleness Compensation in Asynchronous Federated Learning

Probabilistic Client Selection for Asynchronous Wireless Federated Learning

Polaris: Accelerating Asynchronous Federated Learning With Client Selection