A Use of Conjugate Gradient Direction for the Convex Optimization Problem over the Fixed Point Set of a Nonexpansive Mapping
DOI10.1137/070702497zbMath1176.47064OpenAlexW2067313264MaRDI QIDQ3648534
Publication date: 27 November 2009
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/070702497
fixed pointnonexpansive mappingconvex optimization problemhybrid steepest descent methodconjugate gradient direction
Convex programming (90C25) Nonlinear programming (90C30) Variational and other types of inequalities involving nonlinear operators (general) (47J20) Numerical optimization and variational techniques (65K10) Contraction-type mappings, nonexpansive mappings, (A)-proper mappings, etc. (47H09) Methods of reduced gradient type (90C52) Applications of operator theory in numerical analysis (47N40)
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