Gradual Domain Adaptation via Normalizing Flows. (arXiv:2206.11492v1 [stat.ML])

Web: http://arxiv.org/abs/2206.11492

Conventional domain adaptation methods do not work well when a large gap
exists between the source and the target domain. Gradual domain adaptation is
one of the approaches to address the problem by leveraging the intermediate
domain, which gradually shifts from the source to the target domain. The
previous work assumed that the number of the intermediate domains is large and
the distance of the adjacent domains is small; hence, the gradual domain
adaptation algorithm by self-training with unlabeled datasets …

arxiv domain adaptation ml