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cs.LG2003
Reliable and Efficient Inference of Bayesian Networks from Sparse Data by Statistical Learning Theory
Dominik Janzing, Daniel Herrmann
To learn (statistical) dependencies among random variables requires exponentially large sample size in the number of observed random variables if any arbitrary joint probability di…
cs.LG2002
Required sample size for learning sparse Bayesian networks with many variables
Pawel Wocjan, Dominik Janzing, Thomas Beth
Learning joint probability distributions on n random variables requires exponential sample size in the generic case. Here we consider the case that a temporal (or causal) order of…