Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
A key challenge in supporting data-driven scientific applications is the storage and management of input and output data in a distributed environment. In this paper, we describe a...
Stephen Langella, Shannon Hastings, Scott Oster, T...
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Efficient data movement is an important part of any highperformance I/O system, but it is especially critical for the current and next-generation of massively parallel processing ...
Ron Oldfield, Patrick Widener, Arthur B. Maccabe, ...