On Learning Invariant Representation for Domain Adaptation

arXiv: Learning, 2019.

Cited by: 40|Views69
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Abstract:

Due to the ability of deep neural nets to learn rich representations, recent advances in unsupervised domain adaptation have focused on learning domain-invariant features that achieve a small error on the source domain. The hope is that the learnt representation, together with the hypothesis learnt from the source domain, can generalize t...More

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