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In den WarenkorbZustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Hardcover. Zustand: Gut. 2. Auflage. ZUSTAND GUT.
Sprache: Englisch
Verlag: Wiley & Sons, Incorporated, John, 1998
ISBN 10: 0471030031 ISBN 13: 9780471030034
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Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Estimation of Dependences Based on Empirical Data | V. Vapnik | Taschenbuch | Information Science and Statistics | xviii | Englisch | 2010 | Springer | EAN 9781441921581 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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In den WarenkorbZustand: New. In English.
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Sprache: Englisch
Verlag: Springer New York, Humana, 2010
ISBN 10: 1441921583 ISBN 13: 9781441921581
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Twenty- ve years have passed since the publication of the Russian version of the book Estimation of Dependencies Based on Empirical Data (EDBED for short). Twen- ve years is a long period of time. During these years many things have happened. Looking back, one can see how rapidly life and technology have changed, and how slow and dif cult it is to change the theoretical foundation of the technology and its philosophy. I pursued two goals writing this Afterword: to update the technical results presented in EDBED (the easy goal) and to describe a general picture of how the new ideas developed over these years (a much more dif cult goal). The picture which I would like to present is a very personal (and therefore very biased) account of the development of one particular branch of science, Empirical - ference Science. Such accounts usually are not included in the content of technical publications. I have followed this rule in all of my previous books. But this time I would like to violate it for the following reasons. First of all, for me EDBED is the important milestone in the development of empirical inference theory and I would like to explain why. S- ond, during these years, there were a lot of discussions between supporters of the new 1 paradigm (now it is called the VC theory ) and the old one (classical statistics).
Sprache: Englisch
Verlag: Springer New York, Humana, 2006
ISBN 10: 0387308652 ISBN 13: 9780387308654
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Twenty- ve years have passed since the publication of the Russian version of the book Estimation of Dependencies Based on Empirical Data (EDBED for short). Twen- ve years is a long period of time. During these years many things have happened. Looking back, one can see how rapidly life and technology have changed, and how slow and dif cult it is to change the theoretical foundation of the technology and its philosophy. I pursued two goals writing this Afterword: to update the technical results presented in EDBED (the easy goal) and to describe a general picture of how the new ideas developed over these years (a much more dif cult goal). The picture which I would like to present is a very personal (and therefore very biased) account of the development of one particular branch of science, Empirical - ference Science. Such accounts usually are not included in the content of technical publications. I have followed this rule in all of my previous books. But this time I would like to violate it for the following reasons. First of all, for me EDBED is the important milestone in the development of empirical inference theory and I would like to explain why. S- ond, during these years, there were a lot of discussions between supporters of the new 1 paradigm (now it is called the VC theory ) and the old one (classical statistics).
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In den WarenkorbZustand: New. pp. 768.
Zustand: gut. The Nature of Statistical Learning Theory (Information Science and Statistics) In deutscher Sprache. pages.
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Zustand: New. The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. Written in readable and concise style and devoted to key learning problems, the book is intended for statisticians, mathematicia.
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In den WarenkorbZustand: New. A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robot.
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Buch. Zustand: Neu. The Nature of Statistical Learning Theory | V. N. Vapnik | Buch | Information Science and Statistics | xx | Englisch | 1999 | Springer-Verlag GmbH | EAN 9780387987804 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. The Nature of Statistical Learning Theory | Vladimir Vapnik | Taschenbuch | Information Science and Statistics | xx | Englisch | 2010 | Humana | EAN 9781441931603 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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In den WarenkorbZustand: New. pp. 340 Illus.
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 736 pages. 9.75x6.50x1.50 inches. In Stock.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Dez 2000, 2000
ISBN 10: 0387987800 ISBN 13: 9780387987804
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. Neuware -The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 314 pp. Englisch.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Dez 2000, 2000
ISBN 10: 0387987800 ISBN 13: 9780387987804
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: \* the setting of learning problems based on the model of minimizing the risk functional from empirical data \* a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency \* non-asymptotic bounds for the risk achieved using the empirical risk minimization principle \* principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds \* the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: \* the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation \* a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of.