Maximum Density Divergence for Domain Adaptation
IEEE Transactions on Pattern Analysis and Machine Intelligence(2021)
摘要
Unsupervised domain adaptation addresses the problem of transferring knowledge from a well-labeled source domain to an unlabeled target domain where the two domains have distinctive data distributions. Thus, the essence of domain adaptation is to mitigate the distribution divergence between the two domains. The state-of-the-art methods practice this very idea by either conducting adversarial train...
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关键词
Measurement,Training,Kernel,Task analysis,Adaptation models,Benchmark testing,Games
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