529 search results - page 30 / 106 » Optimizing the distribution of large data sets in theory and... |
SODA
2008
ACM
13 years 9 months ago
2008
ACM
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...
PODS
2001
ACM
14 years 7 months ago
2001
ACM
The increasing ability to track and collect large amounts of data with the use of current hardware technology has lead to an interest in the development of data mining algorithms ...
AMCS
2010
13 years 7 months ago
2010
satisfactory network connectivity have dominated this line of research and abstracted away from the mathematical description of the physical processes underlying the observed pheno...
SIGIR
2006
ACM
14 years 1 months ago
2006
ACM
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
CF
2007
ACM
13 years 9 months ago
2007
ACM
In recent years, highly accurate branch predictors have been proposed primarily for high performance processors. Unfortunately such predictors are extremely energy consuming and i...