In this paper, an HMM-embedded unsupervised learning approach is proposed to detect the music events by grouping the similar segments of the music signal. This approach can cluste...
We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex s...
As computing systems grow in complexity, the cluster and grid communities require more sophisticated tools to diagnose, debug and analyze such systems. We have developed a toolkit...
Mark K. Gardner, Wu-chun Feng, Michael Broxton, Ad...
This paper presents a concurrent object model based on distributed recursive sets for data intensive applications that use complex, recursive data layouts. The set abstraction is ...
The application of hardware-parameterized models to distributed systems can result in omission of key bottlenecks such as the full cost of inter-node communication in a shared mem...