The dual IRLS scheme for (hyper-)graph p-Laplacians and ℓp regression with large exponents

We introduce an iterative scheme for discrete convex minimization problems of p-Laplace type such as variational graph p-Laplace problems and ℓp regression. In each iteration, the scheme solves only a weighted least-squares problem. We verify linear convergence for suitably regularized problems and derive convergence to any prescribed tolerance.