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Our training scheme follows the paradigm that in order to effectively derive class labels for the target domain, a network should produce statistically domain invariant embedding, while minimizing the classification error on the labeled source domain.

we aim to preserve the whole structure from source domains and transfer it to serve the task on the target domain. The source and target data are put together for clustering,which simultaneously explores the structures of the source and target domains. The