Learning Sparse Causal Models is not NP-hard

Learning Sparse Causal Models is not NP-hard

26 September 2013

Joris Mooij

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Papers citing "Learning Sparse Causal Models is not NP-hard"

7 / 7 papers shown

Title
Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets Christine W. Bang Vanessa Didelez CML 118 0 0 27 Mar 2025
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 199 444 0 20 Feb 2013
Large-Sample Learning of Bayesian Networks is NP-Hard D. M. Chickering Christopher Meek David Heckerman BDL 129 795 0 19 Oct 2012
An Improved Admissible Heuristic for Learning Optimal Bayesian Networks Changhe Yuan Brandon M. Malone TPM 96 48 0 16 Oct 2012
Maximum likelihood fitting of acyclic directed mixed graphs to binary data R. Evans Thomas S. Richardson 73 25 0 15 Mar 2012
A Logical Characterization of Constraint-Based Causal Discovery Tom Claassen Tom Heskes CML 96 39 0 14 Feb 2012
Bayesian network learning with cutting planes James Cussens 61 258 0 14 Feb 2012