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» Learning Optimal Parameters in Decision-Theoretic Rough Sets
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PVM
2009
Springer
13 years 11 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...
IJRR
2011
126views more  IJRR 2011»
12 years 11 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
13 years 11 months ago
Modeling XCS in class imbalances: population size and parameter settings
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the ...
Albert Orriols-Puig, David E. Goldberg, Kumara Sas...
JCP
2006
78views more  JCP 2006»
13 years 4 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
JCIT
2008
172views more  JCIT 2008»
13 years 4 months ago
Rough Wavelet Hybrid Image Classification Scheme
This paper introduces a new computer-aided classification system for detection of prostate cancer in Transrectal Ultrasound images (TRUS). To increase the efficiency of the comput...
Hala S. Own, Aboul Ella Hassanien