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ICANN
2001
Springer

Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension

9 years 1 months ago
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
Abstract. It has remained an open question whether there exist product unit networks with constant depth that have superlinear VC dimension. In this paper we give an answer by constructing two-hidden-layer networks with this property. We further show that the pseudo dimension of a single product unit is linear. These results bear witness to the cooperative effects on the computational capabilities of product unit networks as they are used in practice.
Michael Schmitt
Added 29 Jul 2010
Updated 29 Jul 2010
Type Conference
Year 2001
Where ICANN
Authors Michael Schmitt
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