The present disclosure relates to a computer implemented method for training a learning model by means of a distributed learning system comprising computing nodes, the computing nodes respectively implementing the learning model and deriving a gradient information for updating the learning model based on training data, the method comprising: encoding, by the respective computing nodes, the gradient information by exploiting a correlation across the gradient information from the respective computing nodes; exchanging, by the respective computing nodes, the encoded gradient information within the distributed learning system; determining an aggregate gradient information based on the encoded gradient information from the respective computing nodes; and updating the learning model of the respective computing nodes with the aggregate gradient information, thereby training the learning model.
Abrahamyan, L & Deligiannis, N, A method for a distributed learning, Patent No. EP3920097.
Abrahamyan, L., & Deligiannis, N. (2021). A method for a distributed learning. (Patent No. EP3920097).
@misc{8ca91eccc922409bb8e66227c24c854a,
title = "A method for a distributed learning",
abstract = "The present disclosure relates to a computer implemented method for training a learning model by means of a distributed learning system comprising computing nodes, the computing nodes respectively implementing the learning model and deriving a gradient information for updating the learning model based on training data, the method comprising: encoding, by the respective computing nodes, the gradient information by exploiting a correlation across the gradient information from the respective computing nodes; exchanging, by the respective computing nodes, the encoded gradient information within the distributed learning system; determining an aggregate gradient information based on the encoded gradient information from the respective computing nodes; and updating the learning model of the respective computing nodes with the aggregate gradient information, thereby training the learning model.",
author = "Lusine Abrahamyan and Nikos Deligiannis",
year = "2021",
language = "English",
type = "Patent",
note = "EP3920097",
}