A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
We overview the development of first-order automated reasoning systems starting from their early years. Based on the analysis of current and potential applications of such systems...
Two of the most important threads of work in knowledge representation today are frame-based representation systems (FRS's) and Bayesian networks (BNs). FRS's provide an ...