Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
Abstract. Artificial systems with a high degree of autonomy require reliable semantic information about the context they operate in. State interpretation, however, is a difficult ...
Daniel Meyer-Delius, Christian Plagemann, Georg vo...
Subgraph patterns are widely used in graph classification, but their effectiveness is often hampered by large number of patterns or lack of discrimination power among individual p...
Several authors have suggested viewing boosting as a gradient descent search for a good fit in function space. At each iteration observations are re-weighted using the gradient of...
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...