Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman
This paper proposes a cooperative approach for composite ontology mapping. We first present an extended classification of automated ontology matching and propose an automatic compo...
In this paper, we present a multi-pronged approach to the "Learning from Example" problem. In particular, we present a framework for integrating learning into a standard...
Jie Sun, Tejas R. Mehta, David Wooden, Matthew Pow...