Theoretical analysis demonstrates stable approximation of variational inequalities in infinite-dimensional Hilbert spaces, indicating robustness against bounded computational errors.
In an infinite-dimensional Hilbert space, we investigate a method for finding a solution of a variational inequality induced by an inverse strongly monotone set-valued mapping. Our results are established in the presence of summable and nonsummable computational errors. We show that our algorithm generates a good approximate solution, if the sequence of computational errors is bounded from above by a constant.
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Alexander J. Zaslavski (2026) studied this question.
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