Paper: Learning From A Substructural Perspective

ACL ID W00-0739
Title Learning From A Substructural Perspective
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

In this paper we study learning from a logical perspective. We show that there is a strong re- lationship between a learning strategy, its for- mal learning framework and its logical represen- tational theory. This relationship enables one to translate learnability results from one theory to another. Moreover if we go from a classi- cal logic theory to a substructural logic theory, we can transform learnability results of logical concepts to results for string languages. In this paper we will demonstrate such a translation by transforming the Valiant learnability result for boolean concepts to a learnability :result for a class of string pattern languages.