Patent ID: 9413779
Filing Date: 2016-08-09
CPC Classification: G06N,H04L

Claim Text:
1. A method comprising: generating local model parameters by training a machine learning model at a device in a computer network using a local data set; identifying, at the device, one or more other devices in the network that have trained machine learning models using remote data sets that are similar to the local data set; transmitting, by the device, the local model parameters to the one or more other devices to cause the one or more other devices to generate performance metrics using the transmitted model parameters: receiving, at the device, the performance metrics from the one or more other devices; receiving, at the device, model parameters from the one or more other devices that were generated by the one or more other devices training one or more other machine learning models; using, by the device, the received model parameters with the local data set to generate local performance metrics; comparing, by the device, the local performance metrics with the performance metrics received from the one or more other devices to select a global set of model parameters; selecting, by the device, the global set of model parameters for the device and the one or more other devices based on the comparison between the local performance metrics and the received performance metrics; and selecting, by the device, the model parameters having the highest average performance metrics as the global set of model parameters.