General inertial proximal stochastic mirror descent algorithm beyond Lipschitz smoothness assumption

In this paper, minimizing the sum of an average of finite proper closed nonconvex functions and a proper lower semicontinuous convex function over a closed convex set, is considered. We propose the general inertial proximal stochastic mirror descent (IPSMD for short) algorithm framework, which not o...

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Veröffentlicht in:	Journal of computational and applied mathematics Jg. 476; S. 117108
Hauptverfasser:	Wang, Shuang, Dong, Xiaomei, Gao, Xue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2026
Schlagworte:	Inertial Mirror descent Nonconvex nonsmooth optimization Proximal gradient descent Variance reduction Mirror descent 49J52 Variance reduction Nonconvex nonsmooth optimization 90C26 90C15 Inertial Proximal gradient descent
ISSN:	0377-0427
Online-Zugang:	Volltext
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