Abstract
In a finite-dimensional Euclidean space, we study the convergence of a proximal point method to a solution of the inclusion induced by a maximal monotone operator, under the presence of computational errors. The convergence of the method is established for nonsummable computational errors. We show that the proximal point method generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.
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Zaslavski, A.J. (2016). Maximal Monotone Operators and the Proximal Point Algorithm. In: Numerical Optimization with Computational Errors. Springer Optimization and Its Applications, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-30921-7_11
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DOI: https://doi.org/10.1007/978-3-319-30921-7_11
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