We present a model for the parallel performance of algorithms that consist of concurrent, two-dimensional wavefronts implemented in a message passing environment. The model combine...
Adolfy Hoisie, Olaf M. Lubeck, Harvey J. Wasserman
—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....
Advances in parallel computation are of central importance to Artificial Intelligence due to the significant amount of time and space their programs require. Functional languages ...
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Skyline queries have attracted considerable attention over the last few years, mainly due to their ability to return interesting objects without the need for user-defined scoring f...