Social Media provide an exciting and novel view into social phenomena. The vast amounts of data that can be gathered from the Internet coupled with massively parallel supercomputer...
William N. Reynolds, Marta S. Weber, Robert M. Far...
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rand...