Distributed training of machine learning models in wireless computing environments

Abstract

An artificial intelligence or machine learning controller generates aggregate machine learning models using models trained by a set of wireless computing devices. A first computing device accesses a set of training data that comprises a set of input data points and a set of output data points. The first computing device trains a first machine learning model using the set of training data and transmits the trained first machine learning model to the controller. The controller generates an aggregate model by aggregating the trained first machine learning model with a plurality of other trained machine learning models that were transmitted to the controller by other computing devices. The aggregate model is sent to the wireless devices or maintained at the controller, and used by either the computing devices or the controller to generate outputs for the devices.