Convergence Rate Analysis of the Proximal Difference of the Convex Algorithm | Zendy

Xueyong Wang | Zendy; Ying Zhang | Zendy; Haibin Chen | Zendy; Xipeng Kou | Zendy

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Convergence Rate Analysis of the Proximal Difference of the Convex Algorithm

Author(s) -

Xueyong Wang,

Ying Zhang,

Haibin Chen,

Xipeng Kou

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/5629868

Subject(s) - mathematics , convex function , rate of convergence , convergence (economics) , convex combination , regular polygon , proper convex function , convex analysis , algorithm , effective domain , function (biology) , convex optimization , mathematical optimization , computer science , key (lock) , geometry , economics , economic growth , evolutionary biology , biology , computer security

In this paper, we study the convergence rate of the proximal difference of the convex algorithm for the problem with a strong convex function and two convex functions. By making full use of the special structure of the difference of convex decomposition, we prove that the convergence rate of the proximal difference of the convex algorithm is linear, which is measured by the objective function value.

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