Meta-learning system for KDD is an open and evolving platform for efficient testing and intelligent recommendation of data mining process. Metalearning is adopted to automate the s...
Many sorting algorithms have been studied in the past, but there are only a few algorithms that can effectively exploit both SIMD instructions and threadlevel parallelism. In this...
Parallel architectures are the way of the future, but are notoriously difficult to program. In addition to the low-level constructs they often present (e.g., locks, DMA, and non-...
We present a case study parallelizing streaming aggregation on three different parallel hardware architectures. Aggregation is a performance-critical operation for data summarizat...
Scott Schneider, Henrique Andrade, Bugra Gedik, Ku...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...