Abstract: The present disclosure provides a computer-implemented method for determining an optimized list of sets of hyperparameter values for application to an additional machine learning task. The method includes obtaining data describing a plurality of different machine learning tasks. The method includes obtaining a plurality of candidate sets of hyperparameter values. The method includes determining an ordered list of sets of hyperparameters selected from the plurality of candidate sets of hyperparameter values, wherein the ordered list of sets of hyperparameters minimizes an aggregate loss over the plurality of different machine learning tasks. The method includes storing the ordered list of sets of hyperparameters for use in training an additional machine learning model to perform an additional machine learning task.