519 citations · 2.1k across the 79 of their papers we have counts for
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cs.LG2012★ 131 cited
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Yuan Shi, Fei Sha
We study the problem of unsupervised domain adaptation, which aims to adapt classifiers trained on a labeled source domain to an unlabeled target domain. Many existing approaches f…
cs.LG2012★ 519 cited
Marginalized Denoising Autoencoders for Domain Adaptation
Minmin Chen, Zhixiang Xu, Kilian Weinberger +1
Stacked denoising autoencoders (SDAs) have been successfully used to learn new representations for domain adaptation. Recently, they have attained record accuracy on standard bench…