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PVM
2009
Springer
14 years 1 months ago
Optimizing MPI Runtime Parameter Settings by Using Machine Learning
Abstract. Manually tuning MPI runtime parameters is a practice commonly employed to optimise MPI application performance on a specific architecture. However, the best setting for ...
Simone Pellegrini, Jie Wang, Thomas Fahringer, Han...
WWW
2011
ACM
13 years 1 months ago
Parallel boosted regression trees for web search ranking
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
BMCBI
2006
158views more  BMCBI 2006»
13 years 6 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
EPS
1995
Springer
13 years 10 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...
MIDDLEWARE
2009
Springer
14 years 1 months ago
A Cost-Sensitive Adaptation Engine for Server Consolidation of Multitier Applications
Abstract. Virtualization-based server consolidation is an important technique for cost and energy reductions in data center environments and a key enabler of cloud computing. Howev...
Gueyoung Jung, Kaustubh R. Joshi, Matti A. Hiltune...