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On subgradient projectors

2014/03/27 by Heinz H. Bauschke, Caifang Wang, Bauschke, Heinz H. +5
Computer Science · Mathematics · #Optimization and Variational Analysis #Advanced Optimization Algorithms Research #Digital Image Processing Techniques

paper · pdf · doi:10.48550/arxiv.1403.7135

Abstract

The subgradient projector is of considerable importance in convex optimization because it plays the key role in Polyak's seminal work - and the many papers it spawned - on subgradient projection algorithms for solving convex feasibility problems. In this paper, we offer a systematic study of the subgradient projector. Fundamental properties such as continuity, nonexpansiveness, and monotonicity are investigated. We also discuss the Yamagishi-Yamada operator. Numerous examples illustrate our results.

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