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The desired estimator gains can be had by handling a convex optimization situation. The correctness and accessibility to the evolved approach tend to be eventually explained via two illustrative examples.Unsupervised domain version (UDA) aims at reducing the distribution discrepancy whenever transferring knowledge from a labeled origin domain to an unlabeled target domain. Previous UDA techniques assume that the origin and target domains share an identical label area, that is unrealistic i

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