Complexity of Computing Generalized VC-Dimensions.
Machine Learning: ECML-94, European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, Proceedings,
, pp.415-418
(1994), [peer-reviewed]
Event Date:
April 6-8, 1994
Abstract / 概要
In the PAC-learning model, the Vapnik-Chervonenkis (VC) dimension plays the key role to estimate the polynomial-sample learnability of a class of binary functions. For a class of {0,…, m}-valued functions, the notion has been generalized in various ways. This paper…