Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
The paper presents an architecture of an anomaly detection system based on the paradigm of artificial immune systems (AISs). Incoming network traffic data are considered by the s...
Abstract. In this paper, we propose a cluster-based cumulative representation for cluster ensembles. Cluster labels are mapped to incrementally accumulated clusters, and a matching...
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possi...
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...