A closed-form matrix regularization parameter for ℓ1-regularized Gaussian MLE, obtained by fixing reselection probability of nonzero entries, matches CV accuracy and support recovery at far lower cost.
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2 Pith papers cite this work, alongside 793 external citations. Polarity classification is still indexing.
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Proposes compatibility scores for bivariate causal statements that quantify plausibility via the confounding implied by the induced multivariate model, plus an incompatibility score based on acyclicity and faithfulness constraints.
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The Regularization Parameter: Sparse Precision Matrix Estimation
A closed-form matrix regularization parameter for ℓ1-regularized Gaussian MLE, obtained by fixing reselection probability of nonzero entries, matches CV accuracy and support recovery at far lower cost.
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Evaluating Bivariate Causal Statements Based on Mutual Compatibility
Proposes compatibility scores for bivariate causal statements that quantify plausibility via the confounding implied by the induced multivariate model, plus an incompatibility score based on acyclicity and faithfulness constraints.