Harmonic and Applied Analysis

From Radon Transforms to Machine Learning

Filippo De Mari, Ernesto De Vito

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English

Springer Nature Switzerland AG
15 December 2022

Complex analysis, complex variables; Differential & Riemannian geometry; Optimisation; Electronics engineering; Databases

Series: Applied and Numerical Harmonic Analysis

Summary
Details

Deep connections exist between harmonic and applied analysis and the diverse yet connected topics of machine learning, data analysis, and imaging science. This volume explores these rapidly growing areas and features contributions presented at the second and third editions of the Summer Schools on Applied Harmonic Analysis, held at the University of Genova in 2017 and 2019. Each chapter offers an introduction to essential material and then demonstrates connections to more advanced research, with the aim of providing an accessible entrance for students and researchers. Topics covered include ill-posed problems; concentration inequalities; regularization and large-scale machine learning; unitarization of the radon transform on symmetric spaces; and proximal gradient methods for machine learning and imaging.

Edited by: Filippo De Mari, Ernesto De Vito
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 2021 ed.
Dimensions: Height: 235mm, Width: 155mm,
Weight: 492g
ISBN: 9783030866662
ISBN 10: 3030866661
Series: Applied and Numerical Harmonic Analysis
Pages: 302
Publication Date: 15 December 2022
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active