Assume that we are given some labelled data points in a source domain. The goal of transfer learning is to reduce the number of labelled data needed in the target domain. The source and target domains are related but not identical. It learns and transfers a model based on the labelled data from the source domain and unlabelled data from the target domain \cite{wang2014active}. There are two types of transfer learning: 1) static transfer learning 2) active transfer learning \cite{wang2014active}.