Semi-supervised domain adaptation via Fredholm integral based kernel methods.
Pattern Recognition, (2019): 185-197
Along with the emergence of domain adaptation in semi-supervised setting, dealing with the noisy and complex data in classifier adaptation underscores its growing importance. We believe a large amount of unlabeled data in target domain, which are always only used in distribution alignment, are more of a great source of information for thi...More
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