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Causal discovery in observational data is crucial to a variety of scientific and business research. Although many causal discovery algorithms have been proposed in recent decades, none of them is effective enough in dealing with high-dimensional discrete data. The main challenge is the complex interactions among large volume of variables, leading to numerous spurious causalities found. In this work,...
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