—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
We present an external-memory algorithm for computing a minimum-cost edit script between two rooted, ordered, labeled trees. The I/O, RAM, and CPU costs of our algorithm are, resp...
— In this paper a clustering algorithm that learns the groups of synchronized spike trains directly from data is proposed. Clustering of spike trains based on the presence of syn...
We consider the execution of a complex application on a heterogeneous "grid" computing platform. The complex application consists of a suite of identical, independent pr...