59 citations · 77 across the 3 of their papers we have counts for
3 papers
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.AI2013★ 59 cited
Gaussian Process Networks
Nir Friedman, Iftach Nachman
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different ca…
cs.LG2012
"Ideal Parent" Structure Learning for Continuous Variable Networks
Iftach Nachman, Gal Elidan, Nir Friedman
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive procedu…