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Found 3 papers, 2 papers with code
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift
Despite extensive literature on dataset shift, limited works address how to efficiently use the auxiliary populations to improve the accuracy of risk evaluation for a given machine learning task in the target population.
Prediction Sets Adaptive to Unknown Covariate Shift
Predicting sets of outcomes -- instead of unique outcomes -- is a promising solution to uncertainty quantification in statistical learning.
Adversarial Meta-Learning of Gamma-Minimax Estimators That Leverage Prior Knowledge
Bayes estimators are well known to provide a means to incorporate prior knowledge that can be expressed in terms of a single prior distribution.
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