New conditional independence assumptions enable mixture proportion estimation and kernel tests for conditional independence without relying on irreducibility.
In the search, we constructed a candidate set of features that satisfies|E[X i |Y= 1]−E[X i |Y=−1]|/ p V[X i |Y= 1]> 1, similarly to D.2.2
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Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
New conditional independence assumptions enable mixture proportion estimation and kernel tests for conditional independence without relying on irreducibility.