Learning-Enabled Estimation: Tight Characterizations under Sample Selection Biases
When can we learn from biased samples? We study regression when outcomes are observed only after passing through selection filters that depend on both covariates and outcomes themselves, a ubiquitous challenge spanning clinical trials with patient dropout, labor markets with self-selection, and auctions with strategic...
Vikram Kher, Jane H. Lee, Anay Mehrotra et al.
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