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» Structural Modelling with Sparse Kernels
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JMLR
2010
155views more  JMLR 2010»
14 years 8 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
ESANN
2004
14 years 11 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
IJCNN
2006
IEEE
15 years 3 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
ACL
2006
14 years 11 months ago
A Hybrid Convolution Tree Kernel for Semantic Role Labeling
A hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (SRL). The hybrid kernel consists of two individual...
Wanxiang Che, Min Zhang, Ting Liu, Sheng Li
JMLR
2011
148views more  JMLR 2011»
14 years 4 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan