We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...
Human-aided computing proposes using information measured directly from the human brain in order to perform useful tasks. In this paper, we extend this idea by fusing computer vis...
Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases s, developers and end users need met...