Multi-source Attention for Unsupervised Domain Adaptation

Understand

Domain adaptation considers the problem of generalising a model learnt using data from a particular source domain to a different target domain.

• Often it is difficult to find a suitable single source to adapt from, and one must consider multiple sources.
• Using an unrelated source can result in sub-optimal performance, known as the \emph{negative transfer}.
• However, it is challenging to select the appropriate source(s) for classifying a given target instance in multi-source unsupervised domain adaptation (UDA).