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Found 2 papers, 2 papers with code
Gradual Source Domain Expansion for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) tries to overcome the need for a large labeled dataset by transferring knowledge from a source dataset, with lots of labeled data, to a target dataset, that has no labeled data.
Ranked #4 on
Domain Adaptation
on Office-31
Backprop Induced Feature Weighting for Adversarial Domain Adaptation with Iterative Label Distribution Alignment
Firstly, it lets the domain classifier focus on features that are important for the classification, and, secondly, it couples the classification and adversarial branch more closely.
Ranked #7 on
Domain Adaptation
on Office-31
