Parametric Proximal-Point Methods

N. Pavel and I. Raykov ()
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N. Pavel: Ohio University
I. Raykov: Ohio University

Journal of Optimization Theory and Applications, 2008, vol. 139, issue 1, No 6, 85-107

Abstract: Abstract The main purpose of the present work is to introduce two parametric proximal-point type algorithms involving the gradient (or subdifferential) of a convex function. We take advantage of some properties of maximal monotone operators to prove monotonicity and convergence rate conditions. One example in Hilbert spaces and two numerical examples with program realizations are presented.

Keywords: Hilbert spaces; Maximal monotone operator; Proximal-point algorithm; Subdifferential (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/s10957-008-9408-0

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