We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
In the incremental versions of Facility Location and k-Median, the demand points arrive one at a time and the algorithm must maintain a good solution by either adding each new dema...
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Obtaining fast and good quality approximations to data distributions is a problem of central interest to database management. A variety of popular database applications including,...
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...