Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Change Point Discovery is a basic algorithm needed in many time series mining applications including rule discovery, motif discovery, casual analysis, etc. Several techniques for c...
Set Cover problems are of core importance in many applications. In recent research, the "red-blue variants" where blue elements all need to be covered whereas red elemen...
Michael Dom, Jiong Guo, Rolf Niedermeier, Sebastia...
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
Protein-protein interactions are critical to many biological processes, extending from the formation of cellular macromolecular structures and enzymatic complexes to the regulation...