Communications of the ACM
Learning Boolean Functions in an Infinite Attribute Space
Machine Learning
On learning visual concepts and DNF formulae
Machine Learning
Unsupervised learning of the morphology of a natural language
Computational Linguistics
Unsupervised learning of morphology using a novel directed search algorithm: taking the first step
MPL '02 Proceedings of the ACL-02 workshop on Morphological and phonological learning - Volume 6
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In this paper, I show that a problem of learning a morphological paradigm is similar to a problem of learning a partition of the space of Boolean functions. I describe several learners that solve this problem in different ways, and compare their basic properties.