Abstract
We study the convergence of a proximal-like minimization algorithm using Bregman functions. We extend the convergence results by Censor and Zenios (1992) and by Chen and Teboulle (1993) by showing that the convergence of the algorithm is preserved in the presence of computational errors.
Citation
Alexander J. Zaslavski. "Convergence of a Proximal-like Algorithm in the Presence of Computational Errors." Taiwanese J. Math. 14 (6) 2307 - 2328, 2010. https://doi.org/10.11650/twjm/1500406077
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