2021
On Recovering from Modeling Errors Using Testing Bayesian Networks
ICML 2021spotlight
We consider the problem of supervised learning with Bayesian Networks when the used dependency structure is incomplete due to missing edges or missing variable states. These modeling errors induce independence constraints on the learned model that may not hold in the true, data-generating distributi…