| Least squares support vector machine classifiers JAK Suykens, J Vandewalle Neural processing letters 9, 293-300, 1999 | 13601 | 1999 |
| Chaos control using least‐squares support vector machines JAK Suykens, J Vandewalle International journal of circuit theory and applications 27 (6), 605-615, 1999 | 5819 | 1999 |
| A multilinear singular value decomposition L De Lathauwer, B De Moor, J Vandewalle SIAM journal on Matrix Analysis and Applications 21 (4), 1253-1278, 2000 | 5176 | 2000 |
| On the Best Rank-1 and Rank-(R1 ,R2 ,. . .,RN) Approximation of Higher-Order Tensors L De Lathauwer, B De Moor, J Vandewalle SIAM journal on Matrix Analysis and Applications 21 (4), 1324-1342, 2000 | 2019 | 2000 |
| Weighted least squares support vector machines: robustness and sparse approximation JAK Suykens, J De Brabanter, L Lukas, J Vandewalle Neurocomputing 48 (1-4), 85-105, 2002 | 1824 | 2002 |
| Benchmarking least squares support vector machine classifiers T Van Gestel, JAK Suykens, B Baesens, S Viaene, J Vanthienen, ... Machine learning 54, 5-32, 2004 | 921 | 2004 |
| Prognostic importance of degree of differentiation and cyst rupture in stage I invasive epithelial ovarian carcinoma I Vergote, J De Brabanter, A Fyles, K Bertelsen, N Einhorn, P Sevelda, ... The lancet 357 (9251), 176-182, 2001 | 800 | 2001 |
| Fetal electrocardiogram extraction by blind source subspace separation L De Lathauwer, B De Moor, J Vandewalle IEEE transactions on biomedical engineering 47 (5), 567-572, 2000 | 794 | 2000 |
| Financial time series prediction using least squares support vector machines within the evidence framework T Van Gestel, JAK Suykens, DE Baestaens, A Lambrechts, G Lanckriet, ... IEEE Transactions on neural networks 12 (4), 809-821, 2001 | 762 | 2001 |
| Optimal control by least squares support vector machines JAK Suykens, J Vandewalle, B De Moor Neural networks 14 (1), 23-35, 2001 | 758 | 2001 |
| Artificial neural networks for modelling and control of non-linear systems JAK Suykens, JPL Vandewalle, BL De Moor Springer Science & Business Media, 2012 | 719 | 2012 |
| On-and off-line identification of linear state-space models M Moonen, B De Moor, L Vandenberghe, J Vandewalle International Journal of Control 49 (1), 219-232, 1989 | 610 | 1989 |
| Recurrent least squares support vector machines JAK Suykens, J Vandewalle IEEE Transactions on Circuits and Systems I: Fundamental Theory and …, 2000 | 576 | 2000 |
| Hash functions based on block ciphers: A synthetic approach B Preneel, R Govaerts, J Vandewalle Advances in Cryptology—CRYPTO’93: 13th Annual International Cryptology …, 1994 | 571 | 1994 |
| Generation of n-double scrolls (n= 1, 2, 3, 4,...) JAK Suykens, J Vandewalle IEEE Transactions on Circuits and Systems I: Fundamental Theory and …, 1993 | 452 | 1993 |
| 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 | 443 | 2002 |
| Propagation characteristics of Boolean functions B Preneel, W Van Leekwijck, L Van Linden, R Govaerts, J Vandewalle Advances in Cryptology—EUROCRYPT’90: Workshop on the Theory and Application …, 1991 | 416 | 1991 |
| Bayesian framework for least-squares support vector machine classifiers, Gaussian processes, and kernel Fisher discriminant analysis T Van Gestel, JAK Suykens, G Lanckriet, A Lambrechts, B De Moor, ... Neural computation 14 (5), 1115-1147, 2002 | 401 | 2002 |
| True random bit generation from a double-scroll attractor ME Yalçin, JAK Suykens, J Vandewalle IEEE Transactions on Circuits and Systems I: Regular Papers 51 (7), 1395-1404, 2004 | 389 | 2004 |
| Multi-valued and universal binary neurons: Theory, learning and applications I Aizenberg, NN Aizenberg, JPL Vandewalle Springer Science & Business Media, 2013 | 384 | 2013 |
Johan SuykensProfessor, KU LeuvenVerified email at esat.kuleuven.be
