« Apprentissage fédéré interentreprises » : différence entre les versions
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''' Cross-Silo Federated Learning''' | ''' Cross-Silo Federated Learning''' | ||
<!- Federated learning (FL) is an emerging technology that enables the training of machine learning models from multiple clients while keeping the data distributed and private. Based on the participating clients and the model training scale, federated learning can be classified into two types: cross-device FL where clients are typically mobile devices and the client number can reach up to a scale of millions; cross-silo FL where clients are organizations or companies and the client number is usually small (e.g., within a hundred). While existing studies mainly focus on cross-device FL, this paper aims to provide an overview of the cross-silo FL. More specifically, we first discuss applications of cross-silo FL and outline its major challenges. We then provide a systematic overview of the existing approaches to the challenges in cross-silo FL by focusing on their connections and differences to cross-device-> | <!-- Federated learning (FL) is an emerging technology that enables the training of machine learning models from multiple clients while keeping the data distributed and private. Based on the participating clients and the model training scale, federated learning can be classified into two types: cross-device FL where clients are typically mobile devices and the client number can reach up to a scale of millions; cross-silo FL where clients are organizations or companies and the client number is usually small (e.g., within a hundred). While existing studies mainly focus on cross-device FL, this paper aims to provide an overview of the cross-silo FL. More specifically, we first discuss applications of cross-silo FL and outline its major challenges. We then provide a systematic overview of the existing approaches to the challenges in cross-silo FL by focusing on their connections and differences to cross-device-> | ||
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Version du 18 avril 2023 à 14:01
Définition
Apprentissage fédéré où les clients sont des organisations ou des entreprises, limitant ainsi le nombre de sources de données (par exemple, moins d'une centaine).
Compléments
La même approche peut être au sein de différents départements d'une même entreprise, ce que les gestionnaires nomment souvent des silos d'après une métaphore calquée de l'anglais.
Français
apprentissage fédéré interentreprises apprentissage fédéré interdépartemental '
Anglais
Cross-Silo Federated Learning
Contributeurs: Patrick Drouin, wiki
