In recent years, co-clustering has emerged as a powerful data mining tool that can analyze dyadic data connecting two entities. However, almost all existing co-clustering techniqu...
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Keeping track of changes in user interests from a document stream with a few relevance judgments is not an easy task. To tackle this problem, we propose a novel method that integr...
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...