Domain Generalization through the Lens of Angular Invariance. (arXiv:2210.15836v1 [cs.LG])

Domain generalization (DG) aims at generalizing a classifier trained on
multiple source domains to an unseen target domain with domain shift. A common
pervasive theme in existing DG literature is domain-invariant representation
learning with various invariance assumptions. However, prior works restrict
themselves to a radical assumption for realworld challenges: If a mapping
induced by a deep neural network (DNN) could align the source domains well,
then such a mapping aligns a target domain as well. In this paper, we simply …

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