Isbn: 9781009769129 - kernel-based methods: milestones and new trends (13 risultati)

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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    Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.

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    Condizione: New. 2026. hardcover. . . . . .

  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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    Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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    Hardcover. Condizione: Brand New. 242 pages. 6.00x0.56x9.00 inches. In Stock.

  • Lingua: Inglese

    Editore: Cambridge University Press Nov 2026, 2026

    100976912X / 9781009769129

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 140,67

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    Buch. Condizione: Neu. Neuware - 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.…

  • Lingua: Inglese

    Editore: Cambridge University Press, Cambridge, 2026

    100976912X / 9781009769129

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    Hardcover. Condizione: new. Hardcover. 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. Kernel methods represent a vibrant area of research with many open questions. The interplay between approximation theory, machine learning, and computational mathematics continues to generate new insights and techniques. This text provides both established results and a window into current research trends aiming to stimulate readers in this field. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Lingua: Inglese

    Editore: Cambridge University Press, Cambridge, 2026

    100976912X / 9781009769129

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    Hardcover. Condizione: new. Hardcover. 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. Kernel methods represent a vibrant area of research with many open questions. The interplay between approximation theory, machine learning, and computational mathematics continues to generate new insights and techniques. This text provides both established results and a window into current research trends aiming to stimulate readers in this field. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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  • Lingua: Inglese

    Editore: Cambridge University Press, 2026

    100976912X / 9781009769129

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    EUR 138,91

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  • Lingua: Inglese

    Editore: Cambridge University Press, Cambridge, 2026

    100976912X / 9781009769129

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    Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    EUR 143,78

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    Hardcover. Condizione: new. Hardcover. 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. Kernel methods represent a vibrant area of research with many open questions. The interplay between approximation theory, machine learning, and computational mathematics continues to generate new insights and techniques. This text provides both established results and a window into current research trends aiming to stimulate readers in this field. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…