FEDERATED TRAINING FOR A NEURAL NETWORK WITH REDUCED COMMUNICATION REQUIREMENT

A method for generating a training contribution for a neural network on a client node for a federated training of the neural network. In the method, a complete set of parameters characterizing the behavior of the neural network is received; the parameterized neural network is supplied with training examples from a predefined set so that the neural network in each case delivers outputs, wherein the training examples are labeled with target outputs; deviations of the outputs from the respective target outputs are evaluated with a predefined cost function; the parameters of the neural network are optimized with the aim of improving the evaluation by the cost function; a set of particularly relevant parameters is selected based on a predefined criterion; for the selected parameters, proposed changes are ascertained as the sought training contribution based on the result of the optimization; the proposed changes are transmitted to a server node.