Personalized federated learning for heterogeneous data: A distributed edge clustering approach

Personalized federated learning for heterogeneous data: A distributed edge clustering approach

Federated learning (FL) is a distributed machine learning technique that allows multiple devices (e.g., smartphones and IoT devices) to collaborate in the training of a shared model with each device preserving the privacy of its local data. However, the highly heterogeneous distribution of data amon...

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Bibliographic Details
Main Authors: Muhammad Firdaus, Siwan Noh, Zhuohao Qian, Harashta Tatimma Larasati, Kyung-Hyune Rhee
Format: Article
Language:English
Published: AIMS Press 2023-04-01
Series:Mathematical Biosciences and Engineering
Subjects:
personalized fl
non-iid data
blockchain
edge computing
client clustering
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023475?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023475?viewType=HTML

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