A method for a distributed learning

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 computing nodes, the gradient information by exploiting a correlation across the gradient information from the respective computing nodes; exchanging, by the computing nodes, the encoded gradient information within the distributed learning system; determining an aggregate gradient information based on the encoded gradient information from the computing nodes; and updating the learning model of the computing nodes with the aggregate gradient information, thereby training the learning model.