Domain Adaptation on the Statistical Manifold

CVPR 2014 Mahsa BaktashmotlaghMehrtash T. HarandiBrian C. LovellMathieu Salzmann

In this paper, we tackle the problem of unsupervised domain adaptation for classification. In the unsupervised scenario where no labeled samples from the target domain are provided, a popular approach consists in transforming the data such that the source and target distributions become similar... (read more)

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