An accelerated preconditioned primal-dual gradient algorithm for structured nonconvex optimization problems

•An novel accelerated preconditioned primal-dual gradient algorithm for solving nonconvex optimization problems by the conjugate duality theory of nonconvex functions.•Our algorithm only needs to calculate the proximal mapping of the conjugate function which is always convex and lower semicontinuous...

Celý popis

Podrobná bibliografia

Vydané v:	Communications in nonlinear science & numerical simulation Ročník 153; s. 109480
Hlavní autori:	Long, Xian-Jun, Nie, Jia-Lin, Gou, Zhun, Sun, Xiang-Kai, Li, Gao-Xi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.02.2026
Predmet:	Conjugate duality theory Global convergence Kurdyka-Łojasiewicz property Primal-dual gradient algorithm Structured nonconvex and nonsmooth problem Structured nonconvex and nonsmooth problem Global convergence Kurdyka-Łojasiewicz property 90C30 90C33 Primal-dual gradient algorithm 90C26 Conjugate duality theory
ISSN:	1007-5704
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!