This paper presents a convex-analytic framework to learn sparse graphs from data. While our problem formulation is inspired by an extension of the graphical lasso using so-called combinatorial graph Laplacian framework, key difference use nonconvex alternative ?1 norm attain with better interpretability. Specifically, we weakly-convex minimax concave penalty (the between and Huber function) whi...