Parameter-based Transfer Learning

The idea behind parameter-based methods is that a well-trained model on the source domain has learned a well-defined structure, and if two tasks are related, this structure can be transferred to the target model.

References

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