We investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically design...
Daniel Cer, Marie-Catherine de Marneffe, Daniel Ju...
Background: While the pairwise alignments produced by sequence similarity searches are a powerful tool for identifying homologous proteins - proteins that share a common ancestor ...
Michael L. Sierk, Michael E. Smoot, Ellen J. Bass,...
We investigate the effect of several adaptive metrics in the context of figure-ground segregation, using Generalized LVQ to train a classifier for image regions. Extending the Euc...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
A new framework is proposed for comparing evaluation metrics in classification applications with imbalanced datasets (i.e., the probability of one class vastly exceeds others). Fo...
Mehrdad Fatourechi, Rabab K. Ward, Steven G. Mason...
In this paper, we present a class of algorithms that use a partial distance metric to speedup the motion estimation process. The partial distance metric is used within the motion ...