For classical domain adaptation methods such as DANN, they enforce uniform alignment to boost the generalization ability of models. However, recent studies have shown that, such uniform alignment can harm domain adaptation performance. To deal with this problem, we incorporate domain taxonomy into domain adaptation process. With domain taxonomy, we can **break** the uniform alignment in domain adaptation. The equilibrium recovers the classic adversarial domain adaptation’s solution if given a non-informative domain taxonomy (e.g., a flat taxonomy where all leaf nodes connect to the root node) while yielding non-trivial results with other taxonomies. See Figure 1 for an example.
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