135 citations · 160 across the 3 of their papers we have counts for
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cs.LG2013★ 18 cited
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm
Nir Friedman, Iftach Nachman, Dana Pe'er
Learning Bayesian networks is often cast as an optimization problem, where the computational task is to find a structure that maximizes a statistically motivated score. By and larg…
cs.LG2012★ 135 cited
Learning Module Networks
Eran Segal, Dana Pe'er, Aviv Regev +2
Methods for learning Bayesian network structure can discover dependency structure between observed variables, and have been shown to be useful in many applications. However, in dom…