On Transfer Learning in Functional Linear Regression. (arXiv:2206.04277v2 [stat.ML] UPDATED)

This work studies the problem of transfer learning under the functional
linear model framework, which aims to improve the fit of the target model by
leveraging the knowledge from related source models. We measure the relatedness
between target and source models using Reproducing Kernel Hilbert Spaces,
allowing the type of knowledge being transferred to be interpreted by the
structure of the spaces. Two algorithms are proposed: one transfers knowledge
when the index of transferable sources is known, while the other …

arxiv linear linear regression regression transfer transfer learning