METHOD FOR SEMI-ASYNCHRONOUS FEDERATED LEARNING AND COMMUNICATION APPARATUS

摘要

The present application provides a method for federated learning. A communication apparatus triggers, by setting a threshold (a time threshold or/and a count threshold), fusion of local models sent by a terminal device, so as to generate a global model, and data characteristics contained in the local models of the terminal device, the degree of lag, and the degree of utilization of a sample set data feature of the corresponding terminal device are comprehensively considered when fusion weights of the local models are designed, such that the problem of low training efficiency caused by a synchronization requirement for model uploading versions in a synchronous system can be avoided, and the problem of unstable convergence and a poor generalization capability caused by an "update upon reception" principle of an asynchronous system can also be avoided.