Discretized-Vapnik-Chervonenkis dimension for analyzing complexity of real function classes

Discretized-Vapnik-Chervonenkis dimension for analyzing complexity of real function classes

In this paper, we introduce the discretized-Vapnik-Chervonenkis (VC) dimension for studying the complexity of a real function class, and then analyze properties of real function classes and neural networks. We first prove that a countable traversal set is enough to achieve the VC dimension for a rea...

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書目詳細資料
Main Authors:	Zhang, Chao, Bian, Wei, Tao, Dacheng, Lin, Weisi
其他作者:	School of Computer Engineering
格式:	Article
語言:	English
出版:	2013
主題:	DRNTU::Engineering::Computer science and engineering
在線閱讀:	https://hdl.handle.net/10356/99545 http://hdl.handle.net/10220/13524
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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