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» Incremental Training of Multiclass Support Vector Machines
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ESANN
2007
15 years 5 months ago
Optimizing kernel parameters by second-order methods
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
Shigeo Abe
136
Voted
ECML
2004
Springer
15 years 9 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
147
Voted
CVPR
2006
IEEE
15 years 7 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
125
Voted
ESANN
2007
15 years 5 months ago
Bat echolocation modelling using spike kernels with Support Vector Regression
Abstract. From the echoes of their vocalisations bats extract information about the positions of reflectors. To gain an understanding of how target position is translated into neu...
Bertrand Fontaine, Herbert Peremans, Benjamin Schr...
127
Voted
ML
2008
ACM
162views Machine Learning» more  ML 2008»
15 years 3 months ago
Incorporating prior knowledge in support vector regression
This paper explores the addition of constraints to the linear programming formulation of the support vector regression problem for the incorporation of prior knowledge. Equality an...
Fabien Lauer, Gérard Bloch