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Averaging Is Probably Not the Optimum Way of Aggregating Parameters in Federated Learning
Federated learning is a decentralized topology of deep learning, that trains a shared model through data distributed among each client (like mobile phones, wearable devices), in order to ensure data privacy by avoiding raw data exposed in data center (server). After each client computes a new model...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516771/ https://www.ncbi.nlm.nih.gov/pubmed/33286088 http://dx.doi.org/10.3390/e22030314 |