Model aggregation techniques in federated learning: A comprehensive survey-Reference-Cited by-同舟云学术

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Model aggregation techniques in federated learning: A comprehensive survey

Published:2024-01 Issue: Volume:150 Page:272-293
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Qi Pian,Chiaro Diletta,Guzzo Antonella,Ianni Michele,Fortino Giancarlo,Piccialli Francesco^ORCID

Funder

Ministero della Salute

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference229 articles.

1. Challenges in deploying machine learning: a survey of case studies;Paleyes;ACM Comput. Surv.,2020

2. Machine learning: Trends, perspectives, and prospects;Jordan;Science,2015

3. Federated learning: Strategies for improving communication efficiency;Konečnỳ,2016

4. Ipls: A framework for decentralized federated learning;Pappas,2021

5. LAFED: A lightweight authentication mechanism for blockchain-enabled federated learning system;Ji;Future Gener. Comput. Syst.,2023

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