Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P, our goal is to find a set C of size k such that the s...
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
In the last decade, spatio-temporal database research focuses on the design of effective and efficient indexing structures in support of location-based queries such as predictive...
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...