Abstract: In this paper, we addressed the limitation of relying solely on distribution alignment and source-domain empirical risk minimization in Unsupervised Domain Adaptation (UDA). Our ...
In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, ...
Abstract: In real-world applications, deep neural networks may encounter constantly changing environments, where the test data originates from continually shifting unlabeled target domains. This ...
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