Many real-world classification tasks involve the prediction of multiple, inter-dependent class labels. A prototypical case of this sort deals with prediction of a sequence of labe...
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
In this paper, we present a heuristic approach for finding errors and possible improvements in business process models. First, we translate the information that is included in a m...
For a finite set of points lying on a lower dimensional manifold embedded in a high-dimensional data space, algorithms have been developed to study the manifold structure. Howeve...
The main challenge of dynamic analysis is the huge volume of data, making it difficult to extract high level views. Most techniques developed so far adopt a finegrained approach ...