Learning Sparse Sharing Architectures for Multiple Tasks

Understand

Most existing deep multi-task learning models are based on parameter sharing, such as hard sharing, hierarchical sharing, and soft sharing.

• How choosing a suitable sharing mechanism depends on the relations among the tasks, which is not easy since it is difficult to understand the underlying shared factors among these tasks.
• In this paper, we propose a novel parameter sharing mechanism, named \emph{Sparse Sharing}.
• Given multiple tasks, our approach automatically finds a sparse sharing structure.