Two fast variance-reduced proximal gradient algorithms for SMVIPs-Stochastic Mixed Variational Inequality Problems with suitable applications to stochastic network games and traffic assignment problems

In this paper, we propose two proximal gradient algorithms with variance reduction for stochastic mixed variational inequality problems. One is a proximal extragradient algorithm and another is a proximal forward–backward–forward algorithm. Under the monotonicity assumption on the mapping F and othe...

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Vydáno v:	Journal of computational and applied mathematics Ročník 408; s. 114132
Hlavní autoři:	Yang, Zhen-Ping, Lin, Gui-Hua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.07.2022
Témata:	Complexity Nonlinear programming Proximal algorithm Stochastic approximation Stochastic mixed variational inequality Variance reduction Stochastic mixed variational inequality 90C33 Proximal algorithm Variance reduction Stochastic approximation 90C15 Nonlinear programming Complexity
ISSN:	0377-0427, 1879-1778
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