Introduction to Nonsmooth Analysis and Optimization

Fuente: arXiv
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Hauptverfasser: Clason, Christian, Valkonen, Tuomo
Format: Preprint
Veröffentlicht: 2020
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author Clason, Christian
Valkonen, Tuomo
author_facet Clason, Christian
Valkonen, Tuomo
contents Functions that are not differentiable in the classical sense have become a central tool in modern mathematical models for imaging, inverse problems, machine learning, and optimal control of differential equations. These models are increasingly formulated in infinite-dimensional function spaces to be independent of problem size and discretization quality. This book presents a unified and rigorous introduction to the infinite-dimensional analysis and algorithmic solution of nonsmooth optimization problems arising from the above-mentioned models, from the necessary theoretical tools of nonsmooth analysis to state-of-the-art algorithms and their convergence and stability analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2001_00216
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Introduction to Nonsmooth Analysis and Optimization
Clason, Christian
Valkonen, Tuomo
Optimization and Control
Functions that are not differentiable in the classical sense have become a central tool in modern mathematical models for imaging, inverse problems, machine learning, and optimal control of differential equations. These models are increasingly formulated in infinite-dimensional function spaces to be independent of problem size and discretization quality. This book presents a unified and rigorous introduction to the infinite-dimensional analysis and algorithmic solution of nonsmooth optimization problems arising from the above-mentioned models, from the necessary theoretical tools of nonsmooth analysis to state-of-the-art algorithms and their convergence and stability analysis.
title Introduction to Nonsmooth Analysis and Optimization
topic Optimization and Control
url https://arxiv.org/abs/2001.00216