A method of meta-learning includes receiving a prediction objective, extracting a plurality of subsets of data from a distributed dataset, generating a plurality of local predictions, wherein each local prediction is based on a different subset of the plurality of subsets of data and the prediction objective, combining the plurality of local predictions, and generating a final prediction based on the combined local predictions.