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CVPR
2006
IEEE
14 years 9 months ago
Efficient Optimal Kernel Placement for Reliable Visual Tracking
This paper describes a novel approach to optimal kernel placement in kernel-based tracking. If kernels are placed at arbitrary places, kernel-based methods are likely to be trappe...
Zhimin Fan, Ming Yang, Ying Wu, Gang Hua, Ting Yu
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,...
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
NIPS
2008
13 years 9 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
ICML
2005
IEEE
14 years 8 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...