Many real world learning problems are best characterized by an interaction of multiple independent causes or factors. Discovering such causal structure from the data is the focus ...
We present a new algorithm for computing the structure of a finite abelian group, which has to store only a fixed, small number of group elements, independent of the group order....
In this paper, we propose a new algorithm for extending the hierarchical clustering methods and introduce a Multi-View Agglomerative Clustering approach to handle multi-view repre...
In this report, we propose a new definition of the E2 DT (Squared Euclidean Distance Transformation) on irregular isothetic grids. We describe a new separable algorithm to compute...
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...