New conditional independence assumptions enable mixture proportion estimation and kernel tests for conditional independence without relying on irreducibility.
For the MPE task, we setn = n′ = 1000and used a Positive-Unlabeled (PU) setting with classpriors (θ, θ′) = (1, 0.5)
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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.