Previous studies of data-driven dependency parsing have shown that the distribution of parsing errors are correlated with theoretical properties of the models used for learning an...
With the advance of the Semantic Web, varying RDF data were increasingly generated, published, queried, and reused via the Web. For example, the DBpedia, a community effort to extr...
This paper presents a novel approach for knowledge mining from a sparse and repeated measures dataset. Genetic programming based symbolic regression is employed to generate multip...
Katya Vladislavleva, Kalyan Veeramachaneni, Matt B...
We present a new method for adaptive surface meshing and triangulationwhichcontrolsthelocallevel–of–detailofthesurface approximation by local spectral estimates. These estimat...
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...