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sample-selection-bias
Robust importance-weighted cross-validation under sample selection bias
Importance-weighted cross-validation produces sub-optimal hyperparameter estimates in problem settings where large weights arise with high probability. We introduce a control variate to increase its robustness to problematically large weights.
14 Oct 2019
University of Pittsburgh, Pittsburgh, PA, USA
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