System and method for asynchronous multi-aspect weighted federated learning

Abstract

System and method for training a federated learning model asynchronously. The system includes a master and K number of institutional clients. The master is configured to execute an aggregation thread and K number of client management threads. The executed k-th client management thread includes: during initialization, instructing a k-th client to initiate a first iteration of training of its local federated learning model to obtain a training event E; or upon receiving an aggregation event Efrom the aggregation thread, instructing the k-th client to perform a t-th iteration of training of the local federated learning model to obtain the training event E; and sending the Eto the aggregation thread. The executed aggregation thread includes: upon receiving E, updating a global federated learning model in the master to obtain the aggregation event E; and sending the Eto the k-th client management thread.