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- W2014763308 abstract "The gradient-projection algorithm (GPA) plays an important role in solving constrained convex minimization problems. Based on Marino and Xu's method [G. Marino and H.-K. Xu, A general method for nonexpansive mappings in Hilbert space, J. Math. Anal. Appl. 318 (2006), pp. 43–52], we combine GPA and averaged mapping approach to propose implicit and explicit composite iterative algorithms for finding a common solution of an equilibrium and a constrained convex minimization problem for the first time in this article. Under suitable conditions, strong convergence theorems are obtained." @default.
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- W2014763308 date "2012-09-10" @default.
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- W2014763308 title "General iterative methods for equilibrium and constrained convex minimization problem" @default.
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- W2014763308 doi "https://doi.org/10.1080/02331934.2012.713361" @default.
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