Adaptive Methods or Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators

S. S. Ablaev; Аблаев С. С.; F. S. Stonyakin; Стонякин Ф. С.; M. S. Alkousa; Алкуса М. С.; D. A. Pasechnyk; Пасечнюк Д. А.

doi:10.31857/S013234742306002X

Adaptive Methods or Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators

Авторлар: Ablaev S.¹^,2, Stonyakin F.¹^,2, Alkousa M.¹^,3, Pasechnyk D.¹^,4
Мекемелер:
1. Moscow Institute of Physics and Technology
2. Vernadsky Crimean Federal University
3. National Research University “Higher School of Economics”
4. Trusted Artificial Intelligence Research Center of ISP RAS
Шығарылым: № 6 (2023)
Беттер: 5-13
Бөлім: DATA ANALYSIS
URL: https://journals.rcsi.science/0132-3474/article/view/148115
DOI: https://doi.org/10.31857/S013234742306002X
EDN: https://elibrary.ru/EIFITN
ID: 148115

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Аннотация

The article is devoted to some adaptive methods for variational inequalities with relatively smooth and relatively strongly monotone operators. Based on the recently proposed proximal version of the extragradient method for this class of problems, we study in detail the method with adaptively selected parameter values. An estimate for the rate of convergence of this method is proved. The result is generalized to a class of variational inequalities with relatively strongly monotone δ-generalized smooth variational inequality operators. For the problem of ridge regression and variational inequality associated with box-simplex games, numerical experiments were performed demonstrating the effectiveness of the proposed method of adaptive selection of parameters during the running of the algorithm.

Әдебиет тізімі

Stonyakin F., Tyurin A., Gasnikov A., Dvurechensky P., Agafonov A., Dvinskikh D., Alkousa M., Pasechnyuk D., Artamonov S., Piskunova V. Inexact Relative Smoothness and Strong Convexity for Optimization and Variational Inequalities by Inexact Model // Optim. Methods and Software. 2021. V. 36. № 6. P. 1155–1201.
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