文章基本信息
- 标题：Polynomial Bounds for VC Dimension of Sigmoidal Neural Networks
- 本地全文：下载
- 作者：Marek Karpinski ; Angus Macintyre
- 期刊名称：Electronic Colloquium on Computational Complexity
- 印刷版ISSN：1433-8092
- 出版年度：1994
- 卷号：1994
- 出版社：Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
- 摘要：
We introduce a new method for proving explicit upper bounds on the VC Dimension of general functional basis networks, and prove as an application, for the first time, the VC Dimension of analog neural networks with the sigmoid activation function (y)=11+e−y to be bounded by a quadratic polynomial in the number of programmable parameters.
- 关键词：Neural Networks; VC Dimension
