A novel Bayesian federated learning framework to address multi-dimensional heterogeneity problem

A novel Bayesian federated learning framework to address multi-dimensional heterogeneity problem

Federated learning (FL) has attracted a lot of interests as a promising machine learning approach to protect user privacy and data security. It requires the clients to send model parameters to the server rather than private datasets, thus protecting privacy to a significant extent. However, there ar...

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Bibliographic Details
Main Authors: Jianye Yang, Tongjiang Yan, Pengcheng Ren
Format: Article
Language:English
Published: AIMS Press 2023-04-01
Series:AIMS Mathematics
Subjects:
federated learning
heterogeneity problem
knowledge distillation
bayesian inference
gaussian probability density function
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2023769?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/math.2023769?viewType=HTML

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