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Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Li, Zilinghan, He, Shilan, Yang, Ze, Ryu, Minseok, Kim, Kibaek, Madduri, Ravi
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Cryptography and Security Distributed, Parallel, and Cluster Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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