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Split: Inferring Unobserved Event Probabilities for Disentangling Brand-Customer Interactions
This paper takes a direct approach whereby an event of interest is identified based on information on the composite event and aggregate data on composite events (e. g. total number of search ads shown).
Dis-entangling Mixture of Interventions on a Causal Bayesian Network Using Aggregate Observations
We study the problem of separating a mixture of distributions, all of which come from interventions on a known causal bayesian network.
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