Work

Communication-Efficient Semi-Decentralized Federated Learning in the Presence of Stragglers

Year: 2025

Type: article

Source: IEEE Transactions on Communications

DOI: 10.1109/tcomm.2025.3605479

Authors: Chengxi Li, Ming Xiao, Mikael Skoglund

Institution: KTH Royal Institute of Technology

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: Digital Futures, Vetenskapsrådet

Awards: Communication-Efficient Decentralized Intelligence in 6G Systems, Coding for Large-scale Distributed Machine Learning

OpenAlex ID: W4413925902

FWCI: 0.825

Cites: 38

Cited by: 2

Related to: 10