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Two-layer accumulated quantized compression for communication-efficient federated learning: TLAQC
Federated learning enables multiple nodes to perform local computations and collaborate to complete machine learning tasks without centralizing private data of nodes. However, the frequent model gradients upload/download operations required by the framework result in high communication costs, which...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356777/ https://www.ncbi.nlm.nih.gov/pubmed/37468562 http://dx.doi.org/10.1038/s41598-023-38916-x |