In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
The ideas of dependency directed backtracking (DDB) and explanation based learning (EBL) have developed independently in constraint satisfaction, planning and problem solving comm...
We formulate a model for probability distributions on image spaces. We show that any distribution of images can be factored exactly into conditional distributions of feature vecto...