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SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities - MaRDI portal

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SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities

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Publication:6413665

arXiv2210.05994MaRDI QIDQ6413665

Author name not available (Why is that?)

Publication date: 12 October 2022

Abstract: Variational inequalities are a broad formalism that encompasses a vast number of applications. Motivated by applications in machine learning and beyond, stochastic methods are of great importance. In this paper we consider the problem of stochastic finite-sum cocoercive variational inequalities. For this class of problems, we investigate the convergence of the method based on the SARAH variance reduction technique. We show that for strongly monotone problems it is possible to achieve linear convergence to a solution using this method. Experiments confirm the importance and practical applicability of our approach.












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