Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice
نویسندگان
چکیده
منابع مشابه
Unsupervised Multi-Domain Adaptation with Feature Embeddings
Representation learning is the dominant technique for unsupervised domain adaptation, but existing approaches have two major weaknesses. First, they often require the specification of “pivot features” that generalize across domains, which are selected by taskspecific heuristics. We show that a novel but simple feature embedding approach provides better performance, by exploiting the feature tem...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2020
ISSN: 0162-8828,2160-9292,1939-3539
DOI: 10.1109/tpami.2020.3036956