Inertial generalized proximal Peaceman-Rachford splitting method for separable convex programming
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Publication:2664392
DOI10.1007/s10092-021-00399-5zbMath1464.90056OpenAlexW3135064523MaRDI QIDQ2664392
Publication date: 20 April 2021
Published in: Calcolo (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10092-021-00399-5
global convergencevariational inequalityconvex programmingPeaceman-Rachford splitting methodindefiniteinertial proximal point
Convex programming (90C25) Nonlinear programming (90C30) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Multi-step inertial strictly contractive PRSM algorithms for convex programming problems with applications ⋮ Convergence analysis of an improved Bregman-type Peaceman-Rachford splitting algorithm for nonconvex nonseparable linearly constrained optimization problems ⋮ A partially inertial customized Douglas-Rachford splitting method for a class of structured optimization problems ⋮ An inertial proximal partially symmetric ADMM-based algorithm for linearly constrained multi-block nonconvex optimization problems with applications
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