Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics (Paperback)

Language: English

Published by Society for Industrial & Applied Mathematics,U.S., New York, 2026

1611979161 / 9781611979169

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Paperback. This monograph develops a unified, application-driven framework for kernel methods grounded in reproducing kernel Hilbert spaces and optimal transport. The primary goal is to tackle industrial cases from computational physics and mathematical finance and discuss applications across various areas, such as statistics, or artificial intelligence (physics-informed systems, reinforcement learning, machine learning, generative methods, etc.).Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics is divided into two parts, theoretical principles and the techniques employed in their applications; contains numerous applications in engineering, finance, and machine learning; and provides a framework for designing numerically efficient, large-scale dataset strategies. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Title
Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics (Paperback)
Author
Philippe G. LeFloch
Publisher
Society for Industrial & Applied Mathematics,U.S., New York
Publication year
2026
Condition
new
Binding
Paperback
Language
English
ISBN 10
1611979161
ISBN 13
9781611979169

CitiRetail

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