Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment

Understand

Unsupervised domain adaptation is effective in leveraging the rich information from the source domain to the unsupervised target domain.

• Though deep learning and adversarial strategy make an important breakthrough in the adaptability of features, there are two issues to be further explored.
• First, the hard-assigned pseudo labels on the target domain are risky to the intrinsic data structure.
• Second, the batch-wise training manner in deep learning limits the description of the global structure.