Despite serious research efforts, automatic ontology matching still suffers from severe problems with respect to the quality of matching results. Existing matching systems trade-of...
Kai Eckert, Christian Meilicke, Heiner Stuckenschm...
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...