Abstract: Multi-task learning ... on the correlation between the outputs. The used features include the intersection, union, and difference between features relevant to each output individually. The ...

Federated Learning (FL) enables joint training across distributed ... Drawing on our theoretical insights into the difference between multi-task and federated optimization, we propose the Hyper ...

To facilitate multi-task training, we define task regret as the difference between the current-stage return and the candidate best one, and adjust the learning weight of each task based on its task ...