Title

Smoothing Techniques and Difference of Convex Functions Algorithms for Image Reconstructions

Published In

Optimization

Document Type

Citation

Publication Date

8-2019

Abstract

In this paper, we study characterizations of differentiability for real-valued functions based on generalized differentiation. These characterizations provide the mathematical foundation for Nesterov's smoothing techniques in infinite dimensions. As an application, we provide a simple approach to image reconstructions based on Nesterov's smoothing and algorithms for minimizing differences of convex (DC) functions that involve the ℓ1−ℓ2 regularization.

Description

Copyright © 2019 Informa UK Limited

DOI

10.1080/02331934.2019.1648467

Persistent Identifier

https://archives.pdx.edu/ds/psu/29649

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