L2M
Learning to Match
**L2M** is a learning algorithm that can work for most cross-domain distribution matching tasks. It automatically learns the cross-domain distribution matching without relying on hand-crafted priors on the matching loss. Instead, L2M reduces the inductive bias by using a meta-network to learn the distribution matching loss in a data-driven way.
Learning to Match Distributions for Domain Adaptation
https://paperswithcode.com/paper/learning-to-match-distributions-for-domain
Learning to Match Distributions for Domain Adaptation