Vapnik, Vladimir Naumovich
Overview
Works:  20 works in 116 publications in 5 languages and 2,964 library holdings 

Roles:  Author, Editor 
Classifications:  Q325.7, 006.31 
Publication Timeline
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Most widely held works by
Vladimir Naumovich Vapnik
Statistical learning theory
by
Vladimir Naumovich Vapnik(
)
12 editions published in 1998 in English and held by 1,044 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
12 editions published in 1998 in English and held by 1,044 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
The nature of statistical learning theory
by
Vladimir Naumovich Vapnik(
Book
)
33 editions published between 1995 and 2010 in English and Chinese and held by 721 WorldCat member libraries worldwide
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 * nonasymptotic 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 LabsResearch and Professor of London University. He is one of the founders of
33 editions published between 1995 and 2010 in English and Chinese and held by 721 WorldCat member libraries worldwide
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 * nonasymptotic 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 LabsResearch and Professor of London University. He is one of the founders of
Estimation of dependences based on empirical data
by
Vladimir Naumovich Vapnik(
)
27 editions published in 2006 in English and held by 555 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
27 editions published in 2006 in English and held by 555 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
Estimation of dependences based on empirical data
by
Vladimir Naumovich Vapnik(
Book
)
17 editions published between 1982 and 2010 in English and held by 305 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
17 editions published between 1982 and 2010 in English and held by 305 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
Empirical Inference : festschrift in honor of Vladimir N. Vapnik
by
Bernhard Schölkopf(
)
2 editions published in 2013 in English and held by 262 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
2 editions published in 2013 in English and held by 262 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
Theorie der Zeichenerkennung : mit 7 Tabellen
by
Vladimir Naumovich Vapnik(
Book
)
3 editions published in 1979 in German and held by 20 WorldCat member libraries worldwide
3 editions published in 1979 in German and held by 20 WorldCat member libraries worldwide
Teorii︠a︡ raspoznavanii︠a︡ obrazov. Stat. problemy obuchenii︠a︡
by
Vladimir Naumovich Vapnik(
Book
)
2 editions published in 1974 in Russian and held by 14 WorldCat member libraries worldwide
2 editions published in 1974 in Russian and held by 14 WorldCat member libraries worldwide
Algoritmy i programmy vosstanovlenii︠a︡ zavisimosteĭ
(
Book
)
1 edition published in 1984 in Russian and held by 11 WorldCat member libraries worldwide
1 edition published in 1984 in Russian and held by 11 WorldCat member libraries worldwide
Teorija raspoznavanija obrazov : statističeskie problemy obučenija
by
Vladimir Naumovich Vapnik(
Book
)
3 editions published in 1974 in Russian and Undetermined and held by 7 WorldCat member libraries worldwide
3 editions published in 1974 in Russian and Undetermined and held by 7 WorldCat member libraries worldwide
Problemy sovremennoĭ kibernetiki
by
Vladimir Naumovich Vapnik(
Book
)
3 editions published in 1975 in Russian and Undetermined and held by 5 WorldCat member libraries worldwide
3 editions published in 1975 in Russian and Undetermined and held by 5 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
Vosstanovlenie zavisimostej po ėmpiričeskim dannym
by
Vladimir Naumovich Vapnik(
Book
)
2 editions published in 1979 in Russian and held by 4 WorldCat member libraries worldwide
2 editions published in 1979 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 3 WorldCat member libraries worldwide
2 editions published in 1973 in Russian and held by 3 WorldCat member libraries worldwide
Sovremennye problemy kibernetiki : sbornik
by
Vladimir Naumovich Vapnik(
Book
)
2 editions published in 1972 in Russian and held by 2 WorldCat member libraries worldwide
2 editions published in 1972 in Russian and held by 2 WorldCat member libraries worldwide
Zadacha obucheniia raspoznavaniiu obrazov
by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 1971 in Russian and held by 2 WorldCat member libraries worldwide
1 edition published in 1971 in Russian and held by 2 WorldCat member libraries worldwide
Tong ji xue xi li lun = Statistical learning theory
by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 2009 in Chinese and held by 1 WorldCat member library worldwide
1 edition published in 2009 in Chinese and held by 1 WorldCat member library worldwide
Teoriâ raspoznavaniâ obrazov : statističeskie problemy obučeniâ
by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 1974 in Russian and held by 1 WorldCat member library worldwide
1 edition published in 1974 in Russian 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
Algoritmy i programmy vosstanovlenija zavisimostej
(
Book
)
1 edition published in 1984 in Russian and held by 1 WorldCat member library worldwide
1 edition published in 1984 in Russian and held by 1 WorldCat member library worldwide
Teorii︠a︡ raspoznavanii︠a︡ obrazov : Statisticheskie problemy obuchenii︠a︡
by
Vladimir Naumovich Vapnik(
Book
)
1 edition published in 1974 in Bulgarian and held by 1 WorldCat member library worldwide
1 edition published in 1974 in Bulgarian and held by 1 WorldCat member library worldwide
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Artificial intelligence Computational learning theory Computer science Cybernetics Distribution (Probability theory) Estimation theory Mathematical optimization Mathematical statistics Mathematics 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
WapnikTscherwonenkis, ... 1936
Wapnik W. N.
Wapnik, W. N. 1936
Wapnik, Wladimir Naumowitsch 1936
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