1 citations · 1 across the 2 of their papers we have counts for
2 papers
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…
math.ST2003★ 1 cited
Selection Criterion for Log-Linear Models Using Statistical Learning Theory
Daniel Herrmann, Dominik Janzing
Log-linear models are a well-established method for describing statistical dependencies among a set of n random variables. The observed frequencies of the n-tuples are explained by…