We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Background: Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be u...