Report on the SVMs' Basics
Kecman V., *High Dimensional Function Approximation (Regression, Hypersurface Fitting) by an Active Set Least Squares Learning Algorithm*, School of Engineering Report 643, The University of Auckland, Auckland, NZ, (53 p.), 2006
Huang T.-M., Kecman V., *Gene extraction for cancer diagnosis by support vector machines - An improvement*, Artificial Intelligence in Medicine (2005) 35, pp. 185-194, Special Issue on Computational Intelligence Techniques in Bioinformatics, 2005
Huang, T.M., Kecman, V., *Semi-supervised
Learning from Unbalanced Labeled Data - An Improvement *, in 'Knowledge
Based and Emergent Technologies Relied Intelligent Information
and Engineering Systems', Eds. Negoita, M. Gh., at al., Lecture
Notes on Computer Science 3215, pp. 765-771, Springer Verlag,
Heidelberg, 2004
Vogt, M., V. Kecman, *Chapter 'Active-Set
Methods for Support Vector Machines'* , in a Springer-Verlag book, 'Support Vector
Machines: Theory and Applications', Ed. L. Wang, 2005
Kecman, V., T. M. Huang, M. Vogt, Chapter *'Iterative
Single Data Algorithm for Training Kernel Machines from Huge
Data Sets: Theory and Performance'* , in a Springer-Verlag book, 'Support
Vector Machines: Theory and Applications', Ed. L. Wang, 2005
Kecman V., Vogt M., Huang T.M., *On
the Equality of Kernel AdaTron and Sequential Minimal Optimization
in Classification and Regression Tasks and Alike Algorithms
for Kernel Machines,* Proceedings
of the ESANN 2003, 11th European Symposium on Artificial Neural
Networks, Bruges, Belgium,
April 23-25, 2003
Kecman V., Hadzic I., *Support Vectors
Selection by Linear Programming*, Proceedings of
the International Joint Conference on Neural Networks (IJCNN
2000), Vol. 5, pp. 193-198, Como, Italy, 2000
Hadzic I., Kecman V., *Support Vector
Machines Trained by Linear Programming. Theory and Application
in Image Compression and Data Classification*, Proceedings
of Neurel 2000, IEEE Fifth Seminar on Neural Network Applications
in Electrical Engineering, pp 18-23, Beograd, Yugoslavia,
2000
Robinson J., Kecman V., *Combining Support Vector Machine Learning with the Discrete Co-sine Transform in Image Compression*, IEEE Transactions on Neural Networks, Vol. 14, No. 4, pp. 950-958, July 2003
Kecman V., Vlacic Lj., Salman R., *Learning
in and performance of the new neural network based adaptive
backthrough control structure*, Proceedings of the
14th IFAC Triennial World Congress, Beijing, PR China,
Vol. K, pp. 133-140, Pergamon, 1999
Kecman V., *Learning in Adaptive Backthrough
Control Structure*, The IEEE Third International
Conference on Algorithms And Architectures for Parallel
Processing (ICA3PP-97), Proc., Melbourne, Australia pp.
611-624, World Scientific, Singapore, 1997
Kecman V., *System Identification Using
Modular Neural Network With Improved Learning*,
The International Workshop on Neural Networks for Identification,
Control, Robotics, and Signal/Image Processing, NICROSPâ€™ 96,
Venice, pp. 40-48, IEEE Computer Society Press 1996
Swider D.J., Browne M.W., Bansal P.K., Kecman V., *Modelling
of Vapour-Compression Liquid Chillers With Neural Networks*,
Journal of Applied Thermal Engineering, Pergamon Press,
Volume 21, Issue 3, pp. 311-329, February 2001
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