The Christoffel–Darboux Kernel for Data Analysis (Cambridge Monographs on Applied and Computational Mathematics)
Jean Bernard Lasserre, Edouard Pauwels, Mihai Putinar
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.
Категории:
Год:
2022
Издание:
New
Издательство:
Cambridge University Press
Язык:
english
Страницы:
188
ISBN 10:
1108838065
ISBN 13:
9781108838061
Файл:
PDF, 5.19 MB
IPFS:
,
english, 2022
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