Kristiaan Pelckmans
Kristiaan Pelckmans
Verified email at it.uu.se - Homepage
TitleCited byYear
LS-SVMlab: a matlab/c toolbox for least squares support vector machines
K Pelckmans, JAK Suykens, T Van Gestel, J De Brabanter, L Lukas, ...
Tutorial. KULeuven-ESAT. Leuven, Belgium 142, 1-2, 2002
3432002
LS-SVMlab toolbox user's guide: version 1.7
K De Brabanter, P Karsmakers, F Ojeda, C Alzate, J De Brabanter, ...
Katholieke Universiteit Leuven, 2010
2582010
Identification of MIMO Hammerstein models using least squares support vector machines
I Goethals, K Pelckmans, JAK Suykens, B De Moor
Automatica 41 (7), 1263-1272, 2005
2342005
Subspace identification of Hammerstein systems using least squares support vector machines
I Goethals, K Pelckmans, JAK Suykens, B De Moor
IEEE Transactions on Automatic Control 50 (10), 1509-1519, 2005
2102005
Handling missing values in support vector machine classifiers
K Pelckmans, J De Brabanter, JAK Suykens, B De Moor
Neural Networks 18 (5-6), 684-692, 2005
1342005
Support vector methods for survival analysis: a comparison between ranking and regression approaches
V Van Belle, K Pelckmans, S Van Huffel, JAK Suykens
Artificial intelligence in medicine 53 (2), 107-118, 2011
792011
LS-SVMlab toolbox user’s guide
K Pelckmans, JAK Suykens, T Van Gestel, J De Brabanter, L Lukas, ...
Pattern recognition letters 24 (2003), 659-675, 2003
792003
Convex clustering shrinkage
K Pelckmans, J De Brabanter, JAK Suykens, B De Moor
PASCAL Workshop on Statistics and Optimization of Clustering Workshop, 2005
602005
Support vector machines for survival analysis
V Van Belle, K Pelckmans, JAK Suykens, S Van Huffel
Proceedings of the Third International Conference on Computational …, 2007
592007
Robustness of kernel based regression: a comparison of iterative weighting schemes
K De Brabanter, K Pelckmans, J De Brabanter, M Debruyne, JAK Suykens, ...
International Conference on Artificial Neural Networks, 100-110, 2009
572009
LS-SVMlab toolbox user’s guide version 1.5
K Pelckmans, JAK Suykens, T Van Gestel, J De Brabanter, L Lukas, ...
Katholiede Univeristeit Leuven, Belgium, unpublished. Available http://www …, 2003
562003
Building sparse representations and structure determination on LS-SVM substrates
K Pelckmans, JAK Suykens, B De Moor
Neurocomputing 64, 137-159, 2005
502005
Least-squares support vector machines for the identification of Wiener–Hammerstein systems
T Falck, P Dreesen, K De Brabanter, K Pelckmans, B De Moor, ...
Control Engineering Practice 20 (11), 1165-1174, 2012
492012
Multi-class kernel logistic regression: a fixed-size implementation
P Karsmakers, K Pelckmans, JAK Suykens
2007 International Joint Conference on Neural Networks, 1756-1761, 2007
442007
Identification of wiener-hammerstein systems using LS-SVMs
T Falck, K Pelckmans, JAK Suykens, B De Moor
IFAC Proceedings Volumes 42 (10), 820-825, 2009
432009
Improved performance on high-dimensional survival data by application of Survival-SVM
V Van Belle, K Pelckmans, S Van Huffel, JAK Suykens
Bioinformatics 27 (1), 87-94, 2010
402010
A comparative study of LS-SVM’s applied to the silver box identification problem
M Espinoza, K Pelckmans, L Hoegaerts, JAK Suykens, B De Moor
IFAC Proceedings Volumes 37 (13), 369-374, 2004
402004
Primal and dual model representations in kernel-based learning
JAK Suykens, C Alzate, K Pelckmans
Statistics Surveys 4, 148-183, 2010
392010
Componentwise least squares support vector machines
K Pelckmans, I Goethals, JD Brabanter, JAK Suykens, BD Moor
Support vector machines: Theory and applications, 77-98, 2005
372005
Additive survival least‐squares support vector machines
V Van Belle, K Pelckmans, JAK Suykens, S Van Huffel
Statistics in Medicine 29 (2), 296-308, 2010
352010
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