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The Christoffel-Darboux Kernel for Data Analysis

Lookup NU author(s): Professor Mihai Putinar


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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.

Publication metadata

Author(s): Lasserre JB, Pauwels E, Putinar M

Publication type: Authored Book

Publication status: Published

Series Title: Cambridge Monographs on Applied and Computational Mathematics

Year: 2022

Number of Pages: 178

Online publication date: 01/03/2022

Acceptance date: 15/12/2020

Publisher: Cambridge University Press

Place Published: Cambridge, UK


Library holdings: Search Newcastle University Library for this item

ISBN: 9781108937078