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» Covariance Kernels from Bayesian Generative Models
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GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
14 years 13 days ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro
ACL
2012
11 years 11 months ago
Crosslingual Induction of Semantic Roles
We argue that multilingual parallel data provides a valuable source of indirect supervision for induction of shallow semantic representations. Specifically, we consider unsupervi...
Ivan Titov, Alexandre Klementiev
CGO
2010
IEEE
14 years 3 months ago
Automatic creation of tile size selection models
Tiling is a widely used loop transformation for exposing/exploiting parallelism and data locality. Effective use of tiling requires selection and tuning of the tile sizes. This is...
Tomofumi Yuki, Lakshminarayanan Renganarayanan, Sa...
LCPC
2004
Springer
14 years 2 months ago
Empirical Performance-Model Driven Data Layout Optimization
Abstract. Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of l...
Qingda Lu, Xiaoyang Gao, Sriram Krishnamoorthy, Ge...
ISMB
1994
13 years 10 months ago
An Improved System for Exon Recognition and Gene Modeling in Human DNA Sequence
A new version of the GRAIL system (Uberbacher and Mural, 1991; Mural et al., 1992; Uberbacher et al., 1993), called GRAILII, has recently been developed (Xu et al., 1994). GRAILII...
Yin Xu, J. Ralph Einstein, Richard J. Mural, Manes...