Preprint
Sep 2026
Summary-powered prediction under distribution shift
This work considers a multi-resolution setting in which individual-level data are available from a source population, while the target population is observed only through subgroup summaries, and proposes SAGE, a one-step estimator that updates a source-trained predictor using a gradient estimated from these summaries.
Ivy Zhang, Dominik Rothenhaeusler
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