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Special issue of DAM on the vapnik-chervonenkis dimension

โœ Scribed by John Shawe-Taylor

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
115 KB
Volume
86
Category
Article
ISSN
0166-218X

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The vapnik-chervonenkis dimension of a r
The vapnik-chervonenkis dimension of a random graph
โœ Martin Anthony; Graham Brightwell; Colin Cooper ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 652 KB

In this paper we investigate a parameter defined for any graph, known as the Vapnik Chervonenkis dimension (VC dimension). For any vertex x of a graph G, the closed neighborhood N(x) of x is the set of all vertices of G adjacent to x, together with x. We say that a set D of vertices of G is shattere

Evaluating the Vapnikโ€“Chervonenkis dimen
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The Vapnik-Chervonenkis (V-C) dimension of a set of functions representing a feed-forward, multi-layered, single output artificial neural network (ANN) with hard-limited activation functions can be evaluated using the Poincare ยดpolynomial of the implied hyperplane arrangement. This ANN is geometrica

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โœ Vitaly Maiorov; Joel Ratsaby ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 872 KB

The degree of approximation of infinite-dimensional function classes using finite n-dimensional manifolds has been the subject of a classical field of study in the area of mathematical approximation theory. In Ratsaby and Maiorov (1997), a new quantity p,(F, L,) which measures the degree of approxim