A sparse LP with sign constraints learns balanced signed graph Laplacians from sample covariance, and an ADMM solver makes each column update linear when observations are scarce.
Sparse inverse covariance estimation with the graphical lasso,
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Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming
A sparse LP with sign constraints learns balanced signed graph Laplacians from sample covariance, and an ADMM solver makes each column update linear when observations are scarce.