Devices, methods, and system for heterogeneous data-adaptive federated learning
Номер патента: EP4118581A1
Опубликовано: 18-01-2023
Автор(ы): Cedric Beliard, Dario Rossi, Lixuan YANG
Принадлежит: Huawei Technologies Co Ltd
Опубликовано: 18-01-2023
Автор(ы): Cedric Beliard, Dario Rossi, Lixuan YANG
Принадлежит: Huawei Technologies Co Ltd
Реферат: The present disclosure relates generally to the field of machine learning. In particular, the disclosure relates to a client computing device and a server computing device for federated machine learning. The client computing device is configured to receive a model comprising a set of common layers and a set of client-specific layers from the server computing device. After a training at the client computing device, the set of common layers and the set of client-specific layers are both updated. The set of updated common layers is sent to the server computing device, and the set of updated client-specific layers is stored at the client computing device. In particular, the server computing device is configured to receive multiple sets of updated common layers from different client computing devices.
Devices, methods, and system for heterogeneous data-adaptive federated learning
Номер патента: WO2021213667A1. Автор: Cedric Beliard,Dario Rossi,Lixuan YANG. Владелец: Huawei Technologies Co., Ltd.. Дата публикации: 2021-10-28.