Federated learning algorithms for generalized mixed-effects model (GLMM) on horizontally partitioned data from distributed sources

OBJECTIVES: This paper developed federated solutions based on two approximation algorithms to achieve federated generalized linear mixed effect models (GLMM). The paper also proposed a solution for numerical errors and singularity issues. And showed the two proposed methods can perform well in revea...

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Detalles Bibliográficos
Autores principales: Li, Wentao, Tong, Jiayi, Anjum, Md. Monowar, Mohammed, Noman, Chen, Yong, Jiang, Xiaoqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9569919/
https://www.ncbi.nlm.nih.gov/pubmed/36244993
http://dx.doi.org/10.1186/s12911-022-02014-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9569919/
https://www.ncbi.nlm.nih.gov/pubmed/36244993
http://dx.doi.org/10.1186/s12911-022-02014-1

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