Learning Weighted Representations for Generalization Across Designs

ICLR 2018 Fredrik D. JohanssonNathan KallusUri ShalitDavid Sontag

Predictive models that generalize well under distributional shift are often desirable and sometimes crucial to building robust and reliable machine learning applications. We focus on distributional shift that arises in causal inference from observational data and in unsupervised domain adaptation... (read more)

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