Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24) - Hardcover
Synopsis
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.
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About the Authors
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.
"About this title" may belong to another edition of this title.
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24)
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24)
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ISBN 13: 9780521865593
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24)
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ISBN 10: 052186559X
ISBN 13: 9780521865593
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Learning Theory: An Approximation Theory Viewpoint (Hardcover)
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Hardcover. Condition: 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521865593
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Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied and Computational Mathematics, Series Number 24)
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Learning Theory: An Approximation Theory Viewpoint (Hardcover)
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ISBN 13: 9780521865593
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Hardcover. Condition: 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521865593
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