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Found 2 papers, 2 papers with code
Detecting hidden confounding in observational data using multiple environments
Under the assumption of independent causal mechanisms underlying the data-generating process, we demonstrate a way to detect unobserved confounders when having multiple observational datasets coming from different environments.
Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
Our question is when using this privileged data leads to more sample-efficient learning of models that use only baseline data for predictions at test time.
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