The original SVM algorithm was invented by Vladimir N. Vapnik and the current standard incarnation ( soft margin ) was proposed by Vapnik and Corinna Cortes in 1995.

In 1995, Corinna Cortes and Vladimir N. Vapnik suggested a modified maximum margin idea that allows for mislabeled examples.

However, in 1992, Bernhard E. Boser, Isabelle M. Guyon and Vladimir N. Vapnik suggested a way to create nonlinear classifiers by applying the kernel trick ( originally proposed by Aizerman et al.

Transductive support vector machines were introduced by Vladimir N. Vapnik in 1998.

A version of SVM for regression was proposed in 1996 by Vladimir N. Vapnik, Harris Drucker, Christopher J. C. Burges, Linda Kaufman and Alexander J. Smola.

* Vapnik, Vladimir N .; The Nature of Statistical Learning Theory, Springer-Verlag, 1995.

* Vapnik, Vladimir N .; and Kotz, Samuel ; Estimation of Dependences Based on Empirical Data, Springer, 2006.

Vladimir Naumovich Vapnik () is one of the main developers of Vapnik – Chervonenkis theory.

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* Vladimir Vapnik ( 1998 ).

Vapnik – Chervonenkis theory ( also known as VC theory ) was developed during 1960 – 1990 by Vladimir Vapnik and Alexey Chervonenkis.

Richard M. Dudley and Vladimir Vapnik himself, among others, apply VC-theory to empirical processes.

It is a core concept in Vapnik – Chervonenkis theory, and was originally defined by Vladimir Vapnik and Alexey Chervonenkis.

Alexey Jakovlevich Chervonenkis (; born 7 September 1938 ) is a Soviet and Russian mathematician, and, with Vladimir Vapnik, was one of the main developers of the Vapnik – Chervonenkis theory, also known as the " fundamental theory of learning " an important part of computational learning theory.

* VC theory, proposed by Vladimir Vapnik ;

* 1995-soft-margin support vector machine algorithm was published by Vladimir Vapnik and Corinna Cortes.