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» Co-Tracking Using Semi-Supervised Support Vector Machines
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CIARP
2010
Springer
15 years 3 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...
ESANN
2004
15 years 7 months ago
Evolutionary tuning of multiple SVM parameters
The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
Frauke Friedrichs, Christian Igel
ICPR
2004
IEEE
16 years 7 months ago
Training of Classifiers Using Virtual Samples Only
This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifiers, a support vector machine and a polynomial c...
Annika Kuhl, Lars Krüger, Christian Wöhl...
ICDAR
2003
IEEE
15 years 11 months ago
Recognition of On-line Handwritten Mathematical Formulas in the E-Chalk System
In this article, we present a system for the recognition of on-line handwritten mathematical formulas which is used in the electronic chalkboard (E-chalk), a multimedia system for...
Ernesto Tapia, Raúl Rojas
ICML
2004
IEEE
16 years 7 months ago
Multi-task feature and kernel selection for SVMs
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
Tony Jebara