We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Many high level representations of time series have been proposed for data mining, including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models etc. Many researc...
Jessica Lin, Eamonn J. Keogh, Li Wei, Stefano Lona...
We study non-parametric measures for the problem of comparing distributions, which arise in anomaly detection for continuous time series. Non-parametric measures take two distribu...
Intrusion detection systems create large amounts of alerts. Significant part of these alerts can be seen as background noise of an operational information system, and its quantity...