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  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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  • Sprache: Englisch

    Verlag: Springer, 2006

    0387308652 / 9780387308654

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    Sprache: Englisch

    Verlag: Springer, 2010

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    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.

  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Zustand: New. pp. 524.

  • Sprache: Englisch

    Verlag: SP SPRINGER, 2006

    0387308652 / 9780387308654

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Zustand: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

  • Sprache: Englisch

    Verlag: Springer, 1982

    0387907335 / 9780387907338

    Serie: Buch 6 von 20 - Information Science and Statistics

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  • Sprache: Englisch

    Verlag: John Wiley & Sons, 1998

    0471030031 / 9780471030034

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    Zustand: 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.

  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 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, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Paperback. Zustand: Brand New. 523 pages. 9.13x5.91x0.39 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 2006

    0387308652 / 9780387308654

    Serie: Buch 6 von 20 - Information Science and Statistics

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    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).

  • Sprache: Englisch

    Verlag: Springer-Verlag Gmbh Dez 2000, 2000

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

    • Hardcover

    Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, DeutschlandBuchWeltWeit Ludwig Meier e.K.

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    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 314 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer-Verlag Gmbh Dez 2000, 2000

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

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    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 314 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer-Verlag Gmbh Dez 2000, 2000

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

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    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.

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    Sprache: Englisch

    Verlag: Springer-Verlag GmbH, 1999

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

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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.

  • Sprache: Englisch

    Verlag: Springer-Verlag Gmbh Dez 2000, 2000

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

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    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

    0387987800 / 9780387987804

    Serie: Buch 17 von 20 - Information Science and Statistics

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    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.

  • Sprache: Englisch

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    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. Written in readable and concise style and devoted to key learning problems, the book is intended for statisticians, mathematicians, physicists, and computer scientists. 314 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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  • Sprache: Englisch

    Verlag: Springer New York, 2006

    0387308652 / 9780387308654

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    Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Afterword of 2006Twenty-?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 ha.

  • Sprache: Englisch

    Verlag: Springer New York, 2010

    1441921583 / 9781441921581

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    Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Afterword of 2006Twenty-?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 ha.

  • Sprache: Englisch

    Verlag: Springer New York Nov 2010, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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). 112 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer New York Mrz 2006, 2006

    0387308652 / 9780387308654

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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). 528 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer New York, Humana Nov 2010, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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).Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer New York, Humana Mär 2006, 2006

    0387308652 / 9780387308654

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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).Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 528 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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    Zustand: New. Print on Demand pp. 524 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

  • Sprache: Englisch

    Verlag: Springer, 2010

    1441921583 / 9781441921581

    Serie: Buch 6 von 20 - Information Science and Statistics

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