An algorithm for combining results of different clusterings is presented in this paper, the objective of which is to find groups of patterns which are common to all clusterings. T...
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
We describe a case study in tit(', application of symbolic machinc learning techniques for the discow;ry of linguistic rules and categories. A supervised rule induction algor...
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...