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We study generalization under labeled shift for categorical and generalnormed label spaces. We propose a series of methods to estimate the importanceweights from labeled source to unlabeled target domain and provide confidencebounds for these estimators. We deploy these estimators and providegeneralization bounds in the unlabeled target domain.

Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift