Multi Source Domain Adaptation by Deep CockTail Networks

Regular domain adaptation (DA) problems are interested in source examples drawn from a single source distribution, yet they probably come from multiple source domains in reality. Compared with DAs, Multi-Source DA (MSDA) is more challenging to settle: The extra domain shifts exist between source domains and moreover, the multi-source domains may also disagree on their semantic information. In this section, we surveyed Deep CockTail Network (DCTN), a prevalent MSDA algorithm that battles the multi-source-derived domain and semantic shifts. The ideology behind is inspired by making cocktails with multiple kinds of stuff (i.e. sources in our background). In particular, DCTN replays two alternating learning phases: (1) DCTN goes through a multi-way adversarial DA process to minimize the domain discrepancy between the target and each source, in order to obtain domain-invariant features. In this …