METHOD FOR EFFICIENT DISTRIBUTED MACHINE LEARNING HYPERPARAMETER SEARCH

摘要

A method of a hyperparameter server improves hyperparameter search efficiency for devices in a self-organizing network (SON) includes sending configuration for data feature collection to at least one edge device in the self-organizing network, receiving hyperparameter performance data from the at least one edge device, and training a shared hyperparameter machine learning model using a global training database including the hyperparameter performance data to identify optimal hyperparameters for use by the at least one edge device. A further method of an edge device improves hyperparameter search efficiency for devices in a SON includes receiving configuration for data feature collection from a hyperparameter server, training an edge machine learning model using local training data and selected hyperparameters, and sending performance data to the hyperparameter server obtained from the training of the edge machine learning model.