The convergence rate analysis of the symmetric ADMM for the nonconvex separable optimization problems | Zendy

Zehui Jia | Zendy; Xue Gao | Zendy; Xingju Cai | Zendy; Deren Han | Zendy

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The convergence rate analysis of the symmetric ADMM for the nonconvex separable optimization problems

Author(s) -

Zehui Jia,

Xue Gao,

Xingju Cai,

Deren Han

Publication year - 2020

Publication title -

journal of industrial and management optimization

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.325

H-Index - 32

eISSN - 1553-166X

pISSN - 1547-5816

DOI - 10.3934/jimo.2020053

Subject(s) - karush–kuhn–tucker conditions , mathematics , rate of convergence , sequence (biology) , separable space , augmented lagrangian method , bounded function , lagrange multiplier , convex function , convergence (economics) , mathematical optimization , function (biology) , multiplier (economics) , regular polygon , computer science , mathematical analysis , computer network , channel (broadcasting) , economics , economic growth , geometry , macroeconomics , evolutionary biology , biology , genetics

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