One of the major limitations of relational learning is due to the complexity of verifying hypotheses on examples. In this paper we investigate this task in light of recent publishe...
With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applica...
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...