coarse procedures or very abstract frames from the point of view of algorithm, because some crucial issues like the representation, evolution, storage, and learning process of conc...
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
The rapid growth of the Internet over the last decade has been startling. However, efforts to track its growth have often fallen afoul of bad data -- for instance, how much traffi...
In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...