Quantitative results on a Halpern-type proximal point algorithm - Leuştean, Laurenţiu; Pinto, Pedro (Computational optimization and applications, 2021)
We apply proof mining methods to analyse a result of Boikanyo and Moroşanu on the strong convergence of a Halpern-type proximal point algorithm. As a consequence, we obtain quantitative versions of this result, providing uniform effective rates of asymptotic regularity and metastability.