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ESANN
2007
13 years 10 months ago
Kernel-based online machine learning and support vector reduction
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
CEC
2007
IEEE
14 years 29 days ago
Support vector machines for computing action mappings in learning classifier systems
XCS with Computed Action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed wi...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
ICML
2003
IEEE
14 years 9 months ago
Low Bias Bagged Support Vector Machines
Theoretical and experimental analyses of bagging indicate that it is primarily a variance reduction technique. This suggests that bagging should be applied to learning algorithms ...
Giorgio Valentini, Thomas G. Dietterich
ML
2007
ACM
130views Machine Learning» more  ML 2007»
13 years 8 months ago
A note on Platt's probabilistic outputs for support vector machines
Platt’s probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an ...
Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
KSEM
2009
Springer
14 years 3 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer