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PerHeFed: A general framework of personalized federated learning for heterogeneous convolutional neural networks
In conventional federated learning, each device is restricted to train a network model of the same structure. This greatly hinders the application of federated learning where the data and devices are quite heterogeneous because of their different hardware equipment and communication networks. At the...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743105/ https://www.ncbi.nlm.nih.gov/pubmed/36531189 http://dx.doi.org/10.1007/s11280-022-01119-x |