« Apprentissage fédéré horizontal » : différence entre les versions
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In the horizontal federated learning setting, multiple clients jointly train a model under the coordination of the central server, while the training data is kept on the client to ensure privacy. | In the horizontal federated learning setting, multiple clients jointly train a model under the coordination of the central server, while the training data is kept on the client to ensure privacy. | ||
Version du 18 avril 2023 à 14:35
en construction
Définition
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Français
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Anglais
Horizontal federated learning
In the horizontal federated learning setting, multiple clients jointly train a model under the coordination of the central server, while the training data is kept on the client to ensure privacy. Horizontal federated learning, or sample-based federated learning, is introduced in the scenarios that data sets share the same feature space but different in sample.
Contributeurs: Patrick Drouin, wiki
