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...
In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...
Contextual advertising supports much of the Web's ecosystem today. User experience and revenue (shared by the site publisher ad the ad network) depend on the relevance of the...
Breaking news often contains timely definitions and descriptions of current terms, organizations and personalities. We utilize such web sources to construct definitions for such t...
Machine learning approaches are frequently used to solve name entity (NE) recognition (NER). In this paper we propose a hybrid method that uses maximum entropy (ME) as the underly...