Before revision: We consider the problem of domain generalization , in which a predictor is trained on data drawn from a family of related training domains and tested on a distinct and unseen test domain.
After revision: We consider the problem of domain generalization , in which a predictor is trained on data drawn from a family of related training domains and then evaluated on a distinct and unseen test domain.