Vapnik, Vladimir Naumovich
Overview
Works:  15 works in 118 publications in 5 languages and 2,532 library holdings 

Roles:  Author, Editor, Honoree 
Classifications:  Q325.7, 006.31015195 
Publication Timeline
.
Most widely held works by
Vladimir Naumovich Vapnik
Statistical learning theory by
Vladimir Naumovich Vapnik(
Book
)
56 editions published between 1995 and 2010 in 3 languages and held by 1,189 WorldCat member libraries worldwide
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 robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to reallife problems, and much more
56 editions published between 1995 and 2010 in 3 languages and held by 1,189 WorldCat member libraries worldwide
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 robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to reallife problems, and much more
Estimation of dependences based on empirical data by
Vladimir Naumovich Vapnik(
Book
)
28 editions published between 1979 and 2006 in 3 languages and held by 80 WorldCat member libraries worldwide
Provides the classical foundation of Statistical Learning Theory. Divided into two parts, this book covers a spectrum of ideas related to the essence of intelligence: from the rigorous statistical foundation of learning models to broad philosophical imperatives for generalization. It is intended for statisticians, mathematicians, and others
28 editions published between 1979 and 2006 in 3 languages and held by 80 WorldCat member libraries worldwide
Provides the classical foundation of Statistical Learning Theory. Divided into two parts, this book covers a spectrum of ideas related to the essence of intelligence: from the rigorous statistical foundation of learning models to broad philosophical imperatives for generalization. It is intended for statisticians, mathematicians, and others
Theorie der Zeichenerkennung by
Vladimir Naumovich Vapnik(
Book
)
4 editions published in 1979 in German and held by 48 WorldCat member libraries worldwide
4 editions published in 1979 in German and held by 48 WorldCat member libraries worldwide
Teorii︠a︡ raspoznavanii︠a︡ obrazov. Stat. problemy obuchenii︠a︡ by
Vladimir Naumovich Vapnik(
Book
)
8 editions published in 1974 in 3 languages and held by 22 WorldCat member libraries worldwide
8 editions published in 1974 in 3 languages and held by 22 WorldCat member libraries worldwide
Algoritmy i programmy vosstanovlenii︠a︡ zavisimosteĭ(
Book
)
3 editions published in 1984 in Russian and held by 14 WorldCat member libraries worldwide
3 editions published in 1984 in Russian and held by 14 WorldCat member libraries worldwide
Empirical inference : festschrift in honor of Vladimir N. Vapnik by
Bernhard Schölkopf(
Book
)
4 editions published in 2013 in English and held by 11 WorldCat member libraries worldwide
This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later developed one of the most successful methods in machine learning, the support vector machine (SVM)  more than just an algorithm, this was a new approach to learning problems, pioneering the use of functional analysis and convex optimization in machine learning. Part I of this book contains three chapters describing and witnessing some of Vladimir Vapnik's contributions to science. In the first chapter, Léon Bottou discusses the seminal paper published in 1968 by Vapnik and Chervonenkis that lay the foundations of statistical learning theory, and the second chapter is an Englishlanguage translation of that original paper. In the third chapter, Alexey Chervonenkis presents a firsthand account of the early history of SVMs and valuable insights into the first steps in the development of the SVM in the framework of the generalised portrait method. The remaining chapters, by leading scientists in domains such as statistics, theoretical computer science, and mathematics, address substantial topics in the theory and practice of statistical learning theory, including SVMs and other kernelbased methods, boosting, PACBayesian theory, online and transductive learning, loss functions, learnable function classes, notions of complexity for function classes, multitask learning, and hypothesis selection. These contributions include historical and context notes, short surveys, and comments on future research directions. This book will be of interest to researchers, engineers, and graduate students engaged with all aspects of statistical learning
4 editions published in 2013 in English and held by 11 WorldCat member libraries worldwide
This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later developed one of the most successful methods in machine learning, the support vector machine (SVM)  more than just an algorithm, this was a new approach to learning problems, pioneering the use of functional analysis and convex optimization in machine learning. Part I of this book contains three chapters describing and witnessing some of Vladimir Vapnik's contributions to science. In the first chapter, Léon Bottou discusses the seminal paper published in 1968 by Vapnik and Chervonenkis that lay the foundations of statistical learning theory, and the second chapter is an Englishlanguage translation of that original paper. In the third chapter, Alexey Chervonenkis presents a firsthand account of the early history of SVMs and valuable insights into the first steps in the development of the SVM in the framework of the generalised portrait method. The remaining chapters, by leading scientists in domains such as statistics, theoretical computer science, and mathematics, address substantial topics in the theory and practice of statistical learning theory, including SVMs and other kernelbased methods, boosting, PACBayesian theory, online and transductive learning, loss functions, learnable function classes, notions of complexity for function classes, multitask learning, and hypothesis selection. These contributions include historical and context notes, short surveys, and comments on future research directions. This book will be of interest to researchers, engineers, and graduate students engaged with all aspects of statistical learning
Problemy sovremennoĭ kibernetiki by
Vladimir Naumovich Vapnik(
Book
)
4 editions published in 1975 in Russian and Undetermined and held by 6 WorldCat member libraries worldwide
4 editions published in 1975 in Russian and Undetermined and held by 6 WorldCat member libraries worldwide
Algoritmy obuchenii︠a︡ raspoznavanii︠u︡ obrazov(
Book
)
1 edition published in 1973 in Russian and held by 4 WorldCat member libraries worldwide
1 edition published in 1973 in Russian and held by 4 WorldCat member libraries worldwide
Ocherki o matematike : sbornik stateĭ(
Book
)
2 editions published in 1973 in Russian and held by 4 WorldCat member libraries worldwide
2 editions published in 1973 in Russian and held by 4 WorldCat member libraries worldwide
Sovremennye problemy kibernetiki : sbornik by
Vladimir Naumovich Vapnik(
Book
)
3 editions published in 1972 in Russian and held by 3 WorldCat member libraries worldwide
3 editions published in 1972 in Russian and held by 3 WorldCat member libraries worldwide
Zadacha obucheniia raspoznavaniiu obrazov by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 1971 in Russian and held by 3 WorldCat member libraries worldwide
1 edition published in 1971 in Russian and held by 3 WorldCat member libraries worldwide
Estimation of dependences based on empirical data : with 22 illustrations by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 1982 in English and held by 1 WorldCat member library worldwide
1 edition published in 1982 in English and held by 1 WorldCat member library worldwide
Structure of statistical learning theory by
Vladimir Naumovich Vapnik(
)
1 edition published in 1996 in English and held by 1 WorldCat member library worldwide
1 edition published in 1996 in English and held by 1 WorldCat member library worldwide
Fibrosis research : methods and protocols by
Vladimir Naumovich Vapnik(
Book
)
in English and held by 1 WorldCat member library worldwide
in English and held by 1 WorldCat member library worldwide
An overview of statistical learning theory by
Vladimir Naumovich Vapnik(
)
1 edition published in 1999 in English and held by 1 WorldCat member library worldwide
1 edition published in 1999 in English and held by 1 WorldCat member library worldwide
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Audience Level
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Related Identities
 Schölkopf, Bernhard Editor
 Luo, Zhiyuan Editor
 Vovk, Vladimir 1960 Editor
 Kotz, Samuel Translator
 Chervonenkis, Aleksei I︠A︡kovlevich
 Červonenkis, Aleksej Ja
 Vapnik, Vladimir Naumovich Informaticien 1935
 Vapnik, Vladimir Naumovich Computer scientist 1935
 Vapnik, Vladimir Naumovich Informatiker 1935
 Chervonenkis, Andreĭ I︠A︡kovlevich
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Associated Subjects
Artificial intelligence Artificial intelligenceMathematical models Computational learning theory Computer science Cybernetics CyberneticsMathematical models Distribution (Probability theory) Estimation theory Mathematical optimization Mathematical statistics Mathematics MathematicsIndustrial applications Optical pattern recognition Pattern perception Probabilities Reasoning Statistics StatisticsComputer programs
Alternative Names
Vapnik, V.
Vapnik, V. 1936
Vapnik, V. N.
Vapnik, Vladimir.
Vapnik, Vladimir 1936
Vapnik, Vladimir N.
Vapnik, Vladimir N. 1936
Vapnik Vladimir Naoumovitch
Vapnik, Vladimir Naumovič 1936
Vapnik Vladimir Naumovich
Vladimir Vapnik
Vladimir Vapnik matematico e statistico sovietico
Vladimir Vapnik mathématicien
Vladimir Vapnik Russisch wiskundige
Vladimir Vapnik Soviet mathematician
WapnikTscherwonenkis, .. 1936
Wapnik W. N.
Wapnik, W. N. 1936
Wapnik, Wladimir Naumowitsch 1936
Wladimir Naumowitsch Wapnik sowjetischamerikanischer Mathematiker
ולדימיר ופניק
ウラジミール・ヴァプニク
弗拉基米尔·万普尼克
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