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Harmonic and Applied Analysis : From Radon Transforms to Machine Learning. 1st ed. 2021.
・ISBN 978-3-030-86663-1 hard EUR 119.99
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| 著者・編者 | De Mari, Filippo / De Vito, Ernesto (eds.), |
|---|---|
| シリーズ | Applied and Numerical Harmonic Analysis |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2021 |
| ページ数 | 302 pp. |
| 言語 | ENG |
| ニュース番号 | <M25-3307> |
解説
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.