Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...