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PVM
2009
Springer
15 years 9 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
14 years 10 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...
156
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BMCBI
2006
158views more  BMCBI 2006»
15 years 3 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
15 years 6 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
15 years 9 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...