Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available b...
The model-driven development of model transformations requires both a technique to model model transformations as well as a means to transform transformation models. Therefore, t...
Finding sparse cuts is an important tool for analyzing large graphs that arise in practice, such as the web graph, online social communities, and VLSI circuits. When dealing with s...
Atish Das Sarma, Sreenivas Gollapudi, Rina Panigra...
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
The intuition behind ensembles is that different prediciton models compensate each other’s errors if one combines them in an appropriate way. In case of large ensembles a lot of...
Krisztian Buza, Alexandros Nanopoulos, Lars Schmid...