Joint Contrastive Learning for Unsupervised Domain Adaptation

18 Jun 2020Changhwa ParkJonghyun LeeJaeyoon YooMinhoe HurSungroh Yoon

Enhancing feature transferability by matching marginal distributions has led to improvements in domain adaptation, although this is at the expense of feature discrimination. In particular, the ideal joint hypothesis error in the target error upper bound, which was previously considered to be minute, has been found to be significant, impairing its theoretical guarantee... (read more)

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