Accelerated variance-reduced methods for saddle-point problems

We consider composite minimax optimization problems where the goal is to find a saddle-point of a large sum of non-bilinear objective functions augmented by simple composite regularizers for the primal and dual variables. For such problems, under the average-smoothness assumption, we propose acceler...

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Vydané v:	EURO journal on computational optimization Ročník 10; s. 100048
Hlavní autori:	Borodich, Ekaterina, Tominin, Vladislav, Tominin, Yaroslav, Kovalev, Dmitry, Gasnikov, Alexander, Dvurechensky, Pavel
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 2022 Elsevier
Predmet:	Accelerated algorithms Composite optimization Minimax optimization Saddle-point problem Stochastic variance-reduced algorithms Minimax optimization Composite optimization Saddle-point problem Accelerated algorithms Stochastic variance-reduced algorithms
ISSN:	2192-4406
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