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ECML
2007
Springer
14 years 1 months ago
Weighted Kernel Regression for Predicting Changing Dependencies
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...
Steven Busuttil, Yuri Kalnishkan
BICOB
2010
Springer
13 years 5 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala
CVPR
2005
IEEE
14 years 9 months ago
Coupled Kernel-Based Subspace Learning
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...
Shuicheng Yan, Dong Xu, Lei Zhang, Benyu Zhang, Ho...
IJCNN
2008
IEEE
14 years 2 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
IJNS
2007
153views more  IJNS 2007»
13 years 7 months ago
Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts
Oligo kernels for biological sequence classification have a high discriminative power. A new parameterization for the K-mer oligo kernel is presented, where all oligomers of lengt...
Britta Mersch, Tobias Glasmachers, Peter Meinicke,...