They assume homogeneous labels and expect the aligned features across domains to behave similarly for the prediction task.
single source adaptation (Chen et al., 2009;Ando and Zhang, 2005;Daumé III, 2009) primarily aims at minimizing the divergence between the source and target domains either at instance or feature levels.