Abstract. Biobanks are gaining in importance by storing large collections of patient's clinical data (e.g. disease history, laboratory parameters, diagnosis, life style) toget...
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
— The paper presents some interim results from an ongoing research on the application of data/text mining methodologies being investigated to modelling the seasonal climate varia...
Subana Shanmuganathan, Ana Perez Kuroki, Ajit Nara...
We present TOURVIZ, a system that helps its users to interactively visualize and make sense in large network datasets. In particular, it takes as input a set of nodes the user spe...
Duen Horng Chau, Leman Akoglu, Jilles Vreeken, Han...