Robust Learning of Fixed-Structure Bayesian Networks
neural information processing systems, pp. 10304-10316, 2018.
polynomial timecomputationally efficientsample complexitybayesian networkslearning algorithmsMore(1+)
We investigate the problem of learning Bayesian networks in a robust model where an ϵ-fraction of the samples are adversarially corrupted. In this work, we study the fully observable discrete case where the structure of the network is given. Even in this basic setting, previous learning algorithms either run in exponential time or lose di...More
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