The Christoffel-Darboux kernel for data analysis:
The Christoffel-Darboux kernel, a central object in approximation theory, is shown to have many potential uses in modern data analysis, including applications in machine learning. This is the first book to offer a rapid introduction to the subject, illustrating the surprising effectiveness of a simp...
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | , |
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2022
|
| Schriftenreihe: | Cambridge monographs on applied and computational mathematics
38 |
| Links: | https://doi.org/10.1017/9781108937078 |
| Zusammenfassung: | The Christoffel-Darboux kernel, a central object in approximation theory, is shown to have many potential uses in modern data analysis, including applications in machine learning. This is the first book to offer a rapid introduction to the subject, illustrating the surprising effectiveness of a simple tool. Bridging the gap between classical mathematics and current evolving research, the authors present the topic in detail and follow a heuristic, example-based approach, assuming only a basic background in functional analysis, probability and some elementary notions of algebraic geometry. They cover new results in both pure and applied mathematics and introduce techniques that have a wide range of potential impacts on modern quantitative and qualitative science. Comprehensive notes provide historical background, discuss advanced concepts and give detailed bibliographical references. Researchers and graduate students in mathematics, statistics, engineering or economics will find new perspectives on traditional themes, along with challenging open problems. |
| Umfang: | 1 Online-Ressource (xv, 168 Seiten) |
| ISBN: | 9781108937078 |
Internformat
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| 520 | |a The Christoffel-Darboux kernel, a central object in approximation theory, is shown to have many potential uses in modern data analysis, including applications in machine learning. This is the first book to offer a rapid introduction to the subject, illustrating the surprising effectiveness of a simple tool. Bridging the gap between classical mathematics and current evolving research, the authors present the topic in detail and follow a heuristic, example-based approach, assuming only a basic background in functional analysis, probability and some elementary notions of algebraic geometry. They cover new results in both pure and applied mathematics and introduce techniques that have a wide range of potential impacts on modern quantitative and qualitative science. Comprehensive notes provide historical background, discuss advanced concepts and give detailed bibliographical references. Researchers and graduate students in mathematics, statistics, engineering or economics will find new perspectives on traditional themes, along with challenging open problems. | ||
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| spelling | Lasserre, Jean-Bernard 1953- The Christoffel-Darboux kernel for data analysis Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar Cambridge Cambridge University Press 2022 1 Online-Ressource (xv, 168 Seiten) txt c cr Cambridge monographs on applied and computational mathematics 38 The Christoffel-Darboux kernel, a central object in approximation theory, is shown to have many potential uses in modern data analysis, including applications in machine learning. This is the first book to offer a rapid introduction to the subject, illustrating the surprising effectiveness of a simple tool. Bridging the gap between classical mathematics and current evolving research, the authors present the topic in detail and follow a heuristic, example-based approach, assuming only a basic background in functional analysis, probability and some elementary notions of algebraic geometry. They cover new results in both pure and applied mathematics and introduce techniques that have a wide range of potential impacts on modern quantitative and qualitative science. Comprehensive notes provide historical background, discuss advanced concepts and give detailed bibliographical references. Researchers and graduate students in mathematics, statistics, engineering or economics will find new perspectives on traditional themes, along with challenging open problems. Pauwels, Edouard 1986- Putinar, Mihai 1955- Erscheint auch als Druck-Ausgabe 9781108838061 |
| spellingShingle | Lasserre, Jean-Bernard 1953- The Christoffel-Darboux kernel for data analysis |
| title | The Christoffel-Darboux kernel for data analysis |
| title_auth | The Christoffel-Darboux kernel for data analysis |
| title_exact_search | The Christoffel-Darboux kernel for data analysis |
| title_full | The Christoffel-Darboux kernel for data analysis Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar |
| title_fullStr | The Christoffel-Darboux kernel for data analysis Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar |
| title_full_unstemmed | The Christoffel-Darboux kernel for data analysis Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar |
| title_short | The Christoffel-Darboux kernel for data analysis |
| title_sort | christoffel darboux kernel for data analysis |
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