Kernel-Based Methods by De Marchi Stefano

Kernel-Based Methods by De Marchi Stefano

Kernel methods, with origins in the pioneering work of Mercer (1909), Bochner (1933), and Aronszajn (1950), have become central tools in modern mathematics and machine learning. This book explores their deep connections with approximation theory, highlighting both classical results and cutting-edge developments. Through clear explanations and illustrative examples, it guides readers from foundational concepts to contemporary applications, including computational methods and real-world problem solving. By bridging theory and practice, the text not only provides a rigorous understanding of kernels but also inspires further exploration and research. Suitable for students, researchers, and practitioners, it invites readers to engage with ongoing advances in this dynamic field and to contribute to its future growth.

'This is an extremely helpful book for researchers who work with kernels in the context of modern applications – including machine learning, image processing, and data scienceIt provides important new theoretical results as well as numerous practical examples, and supplies the necessary software to open up new kernel-based fields of research.' Robert Schaback, University of Göttingen

Stefano De Marchi is Full Professor of Numerical Analysis at the University of Padova. He has authored more than 150 publications and is the managing editor of the open-access journal Dolomites Research Notes on Approximation. He is the founder of the Italian Network on Approximation and one of the discoverers of the so-called Padua points. Francesco Marchetti is Assistant Professor of Numerical Analysis at the University of Padova. His research lies at the intersection of approximation theory and machine learning, focusing on kernel methods and polynomial and RBF interpolation, with applications to medical imaging and space weather forecasting, within national and international research projects. Emma Perracchione is Associate Professor at Politecnico di Torino. Her research focuses on approximation theory and its applications to solar physics, such as astronomical imaging. She is currently Principal Investigator of the GOSSIP project (Greedy Optimal Sampling for Solar Inverse Problems), funded by the Italian Ministry of Universities and Research.

SKU	Unavailable
ISBN 13	9781009769129
Title	Kernel-Based Methods
Author	Stefano De Marchi
Series	Cambridge Monographs On Applied And Computational Mathematics
Condition	Unavailable
Binding Type	Hardback
Publisher	Cambridge University Press
Year published	2026-08-31
Number of pages	242
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.