The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to iden...
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...