Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Learning semantics from annotated images to enhance content-based retrieval is an important research direction. In this paper, annotation data are assumed available for only a sub...
This paper presents ACE (Autonomous Classification Engine), a framework for using and optimizing classifiers. Given a set of feature vectors, ACE experiments with a variety of cla...
Cory McKay, Rebecca Fiebrink, Daniel McEnnis, Bein...
A number of content management tasks, including term categorization, term clustering, and automated thesaurus generation, view natural language terms (e.g. words, noun phrases) as...
Alberto Lavelli, Fabrizio Sebastiani, Roberto Zano...
We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program’s user community. Several example applications illustrat...
Ben Liblit, Alexander Aiken, Alice X. Zheng, Micha...