A joint spectral-radius technique for the product of two ADMM matrices tightens local linear convergence bounds compared with separate norm products.
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods
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New results on the local linear convergence of ADMM: a joint approach
A joint spectral-radius technique for the product of two ADMM matrices tightens local linear convergence bounds compared with separate norm products.