Jeong Un Ryu

MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures

Regularization and transfer learning are two popular techniques to enhance model generalization on unseen data, which is a fundamental problem of machine learning. Regularization techniques are versatile, as they are task- and architecture-agnostic, but they do not exploit a large amount of data ava…