The invention discloses a
federated learning-oriented dynamic personalized
network construction method and device, and the method comprises the following steps: creating a neural
network model, initializing the neural
network model, and transmitting the neural
network model to a
client; performing dynamic calculation on a sample of the
client according to an early-leaving strategy, and finishing updating of an early-leaving layer; selecting an early leaving
strategy execution layer, and selectively sending parameters in the selected early leaving layer; after the
server receives the nodes and the parameters uploaded by the
client, aggregation of the weights of the nodes of the early leaving layer is completed according to an aggregation strategy; and receiving the aggregated parameters from the
server, completing the updating operation of the
model parameters in the client, and completing the construction of the personalized network by means of the updating of the early leaving layer. According to the dynamic personalized
network construction method disclosed by the invention, the reasoning efficiency of the model and the attention of the difficult sample are improved, and the cost of federal learning in sample calculation and model reasoning is reduced while the
personalization of the client model is ensured.