Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. (arXiv:2006.07002v7 [cs.LG] UPDATED)

We study the transfer learning process between two linear regression
problems. An important and timely special case is when the regressors are
overparameterized and perfectly interpolate their training data. We examine a
parameter transfer mechanism whereby a subset of the parameters of the target
task solution are constrained to the values learned for a related source task.
We analytically characterize the generalization error of the target task in
terms of the salient factors in the transfer learning architecture, i.e., the …

arxiv learning linear regression regression transfer learning