Reproducing kernel methods machine von lefloch philippe (5 Ergebnisse)
Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics
Lefloch, Philippe G. (Author)/ Mercier, Jeanmarc (Author)/ Miryusupov, Shohruh (Author)
- Softcover
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Paperback. Zustand: Brand New. 170 pages. In Stock.
Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., New York, 2026
- Softcover
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Paperback. Zustand: new. 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 are…as, 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 multiple locations in the US or from the UK, depending on stock availability.
Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics
LeFloch, Philippe G.; Mercier, Jean-Marc; Miryusupov, Shohruh
Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., 2026
- Softcover
Anbieter: Majestic Books, Hounslow, Vereinigtes KönigreichMajestic Books
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Zustand: New.
Reproducing Kernel Methods for Machine Learning, PDEs, and Statistics
LeFloch, Philippe G.; Mercier, Jean-Marc; Miryusupov, Shohruh
Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., 2026
- Softcover
Anbieter: Books Puddle, New York, NY, USABooks Puddle
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Zustand: New.
Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., New York, 2026
- Softcover
Anbieter: AussieBookSeller, Truganina, VIC, AustralienAussieBookSeller
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Paperback. Zustand: new. 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 are…as, 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
