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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2022
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| Materias: | |
| 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 |