Abstract: There is disclosed a computer-implemented method for training a neural network-based system. The method comprises receiving a training data item and target data associated with the training data item. The training data item is processed using an encoder to generate an encoding of the training data item. A subset of neural networks is selected from a plurality of neural networks stored in a memory based upon the encoding; wherein the plurality of neural networks are configured to process the encoding to generate output data indicative of a classification of an aspect of the training data item. The encoding is processed using the selected subset of neural networks to generate the output data. An update to the parameters of the selected subset of neural networks is determined based upon a loss function comprising a relationship between the generated output data and the target data associated with the training data item.