Previous coreset constructions only allow one missing coordinate.

Unsupervised domain adaptation (UDA)enables cross-domain learning without target domain labels by transferring knowledge from a labeled source domain whose distribution differs from that of the target. However, UDA is not always successful and several accounts of'negative transfer' have been reported in the literature.

The training population typically does not accurately represent what the model will encounter underoperation.

High-level visual brain regions contain subareas in which neurons appear to respond more strongly to examples of a particular semantic category, like faces or bodies, rather than objects. However, recent work has shown that while this finding holds on average, some out-of-category stimuli also activate neurons in these regions.