While the proliferation of sensors being deployed in cell phones, vehicles, buildings,
roadways, and computers allows for larger and more diverse information to be collected, the
cost of acquiring labels for all these data remains extremely high. To overcome the burden of
annotation, alternative solutions have been proposed in the literature to learn decision
making models by exploiting unlabeled data from the same domain (data acquired in similar
conditions as the targeted data) or also data from related but different domains (different …