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Found 2 papers, 1 papers with code
Uneven Bi-Classifier Learning for Domain Adaptation
In this paper, we report that although the generalization ability of the feature extractor can be strengthened by the two even classifiers, the decision boundaries of the two classifiers would be shrank to the source domain in the adversarial process, which weakens the discriminative ability of the learned model.
A Comprehensive Survey on Source-free Domain Adaptation
Over the past decade, domain adaptation has become a widely studied branch of transfer learning that aims to improve performance on target domains by leveraging knowledge from the source domain.
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