Asymptotic Convergence to the Optimal Value of Diagonal Proximal Iterations in Convex Minimization

Given an approximation {f_(n)} of a given objective function f, we provide simple and fairly general conditions under which a diagonal proximal point algorithm approximates the value inf f at a reasonable rate. We also perform some numerical tests and present a short survey on finite convergence