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Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning
Inference of causal structures from observational data is a key component of causal machine learning; in practice, this data may be incompletely observed.
Missing Value Knockoffs
One limitation of the most statistical/machine learning-based variable selection approaches is their inability to control the false selections.
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