A general overview of theoretical foundations; the first book to emphasize the approximation theory viewpoint.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Felipe Cucker is a Professor of Mathematics at the City University of Hong Kong.
Ding Xuan Zhou is an Associate Professor in the Department of Mathematics at the City University of Hong Kong.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: -OnTimeBooks-, Phoenix, AZ, U.S.A.
Condizione: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail. Codice articolo OTV.052186559X.G
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Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9780521865593
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Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9780521865593_new
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
Hardback. Condizione: New. The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines. Codice articolo LU-9780521865593
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. xii + 224. Codice articolo 26405413
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Codice articolo C9780521865593
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. xii + 224 Illus. Codice articolo 7442554
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. xii + 224. Codice articolo 18405423
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 1st edition. 224 pages. 9.00x6.25x0.75 inches. In Stock. Codice articolo x-052186559X
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Da: CitiRetail, Stevenage, Regno Unito
Hardcover. Condizione: new. Hardcover. The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines. The goal of learning theory is to approximate a function from sample values. This is a general overview of the theoretical foundations, and is the first book to emphasize the approximation theory viewpoint. This emphasis provides a balanced approach, and will attract mathematicians to the problems raised. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9780521865593
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