FEDERATED LEARNING METHOD, APPARATUS AND SYSTEM, ELECTRONIC DEVICE, AND STORAGE MEDIUM

The present disclosure provides a federated learning method, apparatus and system, an electronic device, and a storage medium, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision and deep learning technologies. A specific implementation solution includes: performing a plurality of rounds of training until a training end condition is met, so as to obtain a trained global model; and publishing the trained global model to a plurality of devices. Each round of training in the plurality of rounds of training includes: transmitting a current global model to at least some devices in the plurality of devices; receiving trained parameters for the current global model from the at least some devices; performing an aggregation on the received parameters to obtain a current aggregation model; and adjusting the current aggregation model based on a globally shared dataset, and updating the adjusted aggregation model as a new current global model for a next round of training.