Review on heterogeneous transfer learning - Yingzhao ZHU (Dianxin kexue)
Heterogeneous transfer learning breaks through the boundary that the feature space of source domain and target domain must be the same.It realizes analysis mining and knowledge migration of heterogeneous data.It further promotes data reuse and opens up a wider range of applications for the field of machine learning.Firstly,the definition and classification of transfer learning was introduced.Then,the research status of heterogeneous transfer learning was elaborated and its application scenarios were analyzed.At last,the existing problems and the possible research direction in the future were pointed out.