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Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively train a machine learning model without having them share their private data. Recent research, h
Externí odkaz:
http://arxiv.org/abs/2310.02113
Autor:
Leticia Rovira
Publikováno v:
Anuario Digital (Escuela de Historia. Facultad de Humanidades y Artes. Universidad Nacional de Rosario), Vol 0, Iss 22, Pp 291-295 (2011)
Externí odkaz:
https://doaj.org/article/c917506f6d014186804f54be2882e63b
Autor:
Candelaria, Myrna, Villela, Luis, Oñate-Ocana, Luis F., Beltran, Brady, Torres-Viera, Maria, Oliver, Ana, Idrobo, Henry, Perez-Jacobo, Fernando, Perini, Guilherme, Peña, Camila, Korin, Laura, Castro, Denisse, Irigoyen, Victoria, Paredes, Sally, Hernandez-Hernandez, Jose A., Colunga, Perla, Gomez-Almaguer, David, Ruiz-Argüelles, Guillermo, Otañez, Melani, Castillo, Jorge J., Malpica, Luis
Publikováno v:
In Journal of Geriatric Oncology January 2025 16(1)
Autor:
Pérez-Pascual, Daniel, Jiménez-Guillen, Doribet, Santamaría-Poot, Lourdes María, Cime-Castillo, Jorge, Zúñiga-Aguilar, José Juan
Publikováno v:
In South African Journal of Botany January 2025 176:49-61
Autor:
Crespo-Quintanilla, Jesús A., García-Castillo, Jorge L., I. Minchaca-Mojica, Jesús, Picón-Núñez, Martín
Publikováno v:
In Thermal Science and Engineering Progress September 2024 54
Publikováno v:
In Chemical Engineering and Processing - Process Intensification May 2024 199
Autor:
Argotte-Ramos, Rocío, Cime-Castillo, Jorge, Vargas, Valeria, Lanz-Mendoza, Humberto, Rodriguez, Mario H., Rodriguez, Maria Carmen
Publikováno v:
In Heliyon 30 April 2024 10(8)
Publikováno v:
In Blood 25 April 2024 143(17):1702-1712