| Summary: | Heterogeneous domain adaptation (HDA) aims to assist the modeling tasks of the target domain lied in different spaces with knowledge of the source domain. A core issue of HDA is how to preserve the information of the original data during domain adaptation and eliminate the information loss caused by feature transformation. This paper proposes a joint information preservation (JIP) method to deal with the problem. The method preserves the information of the original data from two aspects. On the one hand, large number of paired samples often exist between the two domains of the HDA and the proposed method preserves the paired information by maximizing the correlation of the paired samples. On the other hand, the proposed method improves the strategy of preserving the structural information of the original data, where the local and global structural information are preserved simultaneously. Finally, the JIP is integrated with distribution matching to achieve HDA tasks. Experimental results show the superiority of the proposed method over the state-of-the-art HDA algorithms.
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