Harmonic and Applied Analysis

From Radon Transforms to Machine Learning

Filippo De Mari, Ernesto de Vito (Herausgeber)

Buch | Softcover

XV, 302 Seiten

2022 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-86666-2 (ISBN)

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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.

Bartolucci, F., De Mari, F., Monti, M., Unitarization of the Horocyclic Radon Transform on Symmetric Spaces.- Maurer, A., Entropy and Concentration.-Alaifari, R., Ill-Posed Problems: From Linear to Non-Linear and Beyond.- Salzo, S., Villa, S., Proximal Gradient Methods for Machine Learning and Imaging.- De Vito, E., Rosasco, L., Rudi, A., Regularization: From Inverse Problems to Large Scale Machine Learning.

Erscheinungsdatum	16.12.2022
Reihe/Serie	Applied and Numerical Harmonic Analysis
Zusatzinfo	XV, 302 p. 25 illus., 14 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	486 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Analysis
Schlagworte	applied harmonic analysis • concentration inequalities • Harmonic Analysis machine learning • Ill-posed problems machine learning • Imaging Science • Radon Transform
ISBN-10	3-030-86666-1 / 3030866661
ISBN-13	978-3-030-86666-2 / 9783030866662
Zustand	Neuware