Theconventional closed-set DAmethods generally assume that the source and target domains share the same label space. However, this assumption is often not realistic in practice.

Unsupervised domain adaptation has attracted appealing academic attentions by transferring knowledge from labeled source domain to unlabeled target domain.

Adapting to dynamic data distributions is a practical yet challenging task.

Westudy linear regression under covariate shift, where themarginal distribution over the input covariates differs in the source and the target domains, while the conditional distribution of the output given the input covariates is similar across thetwodomains.