A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...
We present a methodology to automatically generate an online job scheduling method for a custom-made objective and real workloads. The scheduling problem comprises independent para...
Carsten Franke, Joachim Lepping, Uwe Schwiegelshoh...