Instance-based Transfer Learning

Instance-based transfer learning methods try to reweight the samples in the source domain in an attempt to correct for marginal distribution differences. These reweighted instances are then directly used in the target domain for training.

References

Georgian Impact Blog. (n.d.). Transfer Learning Part 1. Link.