The intuition that different text classifiers behave in qualitatively different ways has long motivated attempts to build a better metaclassifier via some combination of classifie...
Web image search using text queries has received considerable attention. However, current state-of-the-art approaches require training models for every new query, and are therefore...
Josip Krapac, Moray Allan, Jakob Verbeek, Frédér...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...