A method for decentralized multi-task learning includes publishing metadata associated with a first task. A plurality of parameter vectors associated with a set of similar tasks to the first task is obtained and the set of similar tasks is associated with a plurality of other participants. A parameter vector associated with a machine learning dataset for the first task is trained based on a loss function associated with the first task and the plurality of parameter vectors associated with the set of similar tasks. The parameter vector associated with the machine learning dataset for the first task is published.
DECENTRALIZED MULTI-TASK LEARNING