We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
This article deals with the recognition of recurring multivariate time series patterns modelled sample-point-wise by parametric fuzzy sets. An efficient classification-based approa...
In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particul...
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Given multivariate time series, we study the problem of forming portfolios with maximum mean reversion while constraining the number of assets in these portfolios. We show that it...
We introduce robust regression-based online filters for multivariate time series and discuss their performance in real time signal extraction settings. We focus on methods that ca...
A problem of association rules discovery in a multivariate time series is considered in this paper. A method for finding interpretable association rules between frequent qualitati...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
The analysis of time series is a central issue in economic research and many other scientific applications. However, the data management functionality for this field is not provid...
Werner Dreyer, Angelika Kotz Dittrich, Duri Schmid...
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 ...