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Type: Artigo
Title: Epsilon-subgradient Algorithms For Bilevel Convex Optimization
Author: Helou
Elias S.; Simoes
Lucas E. A.
Abstract: This paper introduces and studies the convergence properties of a new class of explicit e-subgradient methods for the task of minimizing a convex function over a set of minimizers of another convex minimization problem. The general algorithm specializes to some important cases, such as first-order methods applied to a varying objective function, which have computationally cheap iterations. We present numerical experimentation concerning certain applications where the theoretical framework encompasses efficient algorithmic techniques, enabling the use of the resulting methods to solve very large practical problems arising in tomographic image reconstruction.
Subject: Epsilon-subgradient Methods
Bilevel Optimization
Tomographic Image Reconstruction
Editor: IOP Publishing Ltd
Rights: fechado
Identifier DOI: 10.1088/1361-6420/aa6136
Date Issue: 2017
Appears in Collections:Unicamp - Artigos e Outros Documentos

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