Hybrid SGD algorithms to solve stochastic composite optimization problems with application in sparse portfolio selection problems

In this paper, we study stochastic composite problems where the objective can be the composition of an outer single-valued function and an inner vector-valued mapping. In this stochastic composite optimization, the inner mapping can be expressed as an expectation over random component mappings. In t...

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Vydané v:	Journal of computational and applied mathematics Ročník 436; s. 115425
Hlavní autori:	Yang, Zhen-Ping, Zhao, Yong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 15.01.2024
Predmet:	Complexity Hybrid stochastic estimator Normalized proximal gradient algorithm Prox-linear algorithm Stochastic nonsmooth composite optimization 68W20 68Q25 Stochastic nonsmooth composite optimization 90C26 Hybrid stochastic estimator Normalized proximal gradient algorithm Prox-linear algorithm Complexity
ISSN:	0377-0427, 1879-1778
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