Coupling the Proximal Point Algorithm with Approximation Methods

R. Cominetti
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R. Cominetti: Universidad de Chile

Journal of Optimization Theory and Applications, 1997, vol. 95, issue 3, No 6, 600 pages

Abstract: Abstract We study the convergence of a diagonal process for minimizing a closed proper convex function f, in which a proximal point iteration is applied to a sequence of functions approximating f. We prove that, when the approximation is sufficiently fast, and also when it is sufficiently slow, the sequence generated by the method converges toward a minimizer of f. Comparison to previous work is provided through examples in penalty methods for linear programming and Tikhonov regularization.

Keywords: Proximal point algorithm; steepest descent; penalty methods; viscosity methods; convex optimization (search for similar items in EconPapers)
Date: 1997
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Citations: View citations in EconPapers (6)

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DOI: 10.1023/A:1022621905645

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