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Idioma: Inglés
Publicado por Birkhauser Verlag AG, Basel, 2024
ISBN 10: 3031514610 ISBN 13: 9783031514616
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
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Añadir al carritoPaperback. Condición: new. Paperback. Metric algebraic geometry combines concepts from algebraic geometry and differential geometry. Building on classical foundations, it offers practical tools for the 21st century. Many applied problems center around metric questions, such as optimization with respect to distances.After a short dive into 19th-century geometry of plane curves, we turn to problems expressed by polynomial equations over the real numbers. The solution sets are real algebraic varieties. Many of our metric problems arise in data science, optimization and statistics. These include minimizing Wasserstein distances in machine learning, maximum likelihood estimation, computing curvature, or minimizing the Euclidean distance to a variety.This book addresses a wide audience of researchers and students and can be used for a one-semester course at the graduate level. The key prerequisite is a solid foundation in undergraduate mathematics, especially in algebra and geometry. This is an openaccess book. Metric algebraic geometry combines concepts from algebraic geometry and differential geometry. Many applied problems center around metric questions, such as optimization with respect to distances.After a short dive into 19th-century geometry of plane curves, we turn to problems expressed by polynomial equations over the real numbers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoCondición: New. 2024th edition NO-PA16APR2015-KAP.
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Añadir al carritoPaperback. Condición: Brand New. 229 pages. 9.25x6.10x0.49 inches. In Stock.
Idioma: Inglés
Publicado por Birkhauser Verlag AG, Basel, 2024
ISBN 10: 3031514610 ISBN 13: 9783031514616
Librería: AussieBookSeller, Truganina, VIC, Australia
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Añadir al carritoPaperback. Condición: new. Paperback. Metric algebraic geometry combines concepts from algebraic geometry and differential geometry. Building on classical foundations, it offers practical tools for the 21st century. Many applied problems center around metric questions, such as optimization with respect to distances.After a short dive into 19th-century geometry of plane curves, we turn to problems expressed by polynomial equations over the real numbers. The solution sets are real algebraic varieties. Many of our metric problems arise in data science, optimization and statistics. These include minimizing Wasserstein distances in machine learning, maximum likelihood estimation, computing curvature, or minimizing the Euclidean distance to a variety.This book addresses a wide audience of researchers and students and can be used for a one-semester course at the graduate level. The key prerequisite is a solid foundation in undergraduate mathematics, especially in algebra and geometry. This is an openaccess book. Metric algebraic geometry combines concepts from algebraic geometry and differential geometry. Many applied problems center around metric questions, such as optimization with respect to distances.After a short dive into 19th-century geometry of plane curves, we turn to problems expressed by polynomial equations over the real numbers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Metric algebraic geometry combines concepts from algebraic geometry and differential geometry. Building on classical foundations, it offers practical tools for the 21st century. Many applied problems center around metric questions, such as optimization with respect to distances.After a short dive into 19th-century geometry of plane curves, we turn to problems expressed by polynomial equations over the real numbers. The solution sets are real algebraic varieties. Many of our metric problems arise in data science, optimization and statistics. These include minimizing Wasserstein distances in machine learning, maximum likelihood estimation, computing curvature, or minimizing the Euclidean distance to a variety.This book addresses a wide audience of researchers and students and can be used for a one-semester course at the graduate level. The key prerequisite is a solid foundation in undergraduate mathematics, especially in algebra and geometry. This is an openaccess book.
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Idioma: Inglés
Publicado por Springer Nature Switzerland, 2024
ISBN 10: 3031514610 ISBN 13: 9783031514616
Librería: moluna, Greven, Alemania
EUR 38,69
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. brings algebraic and differential geometry together in a computational settingprovides a modern view on this connection, motivated by data science and AIfocuses on concrete examples from a wide variety of applicationsThis book is ope.