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Johan A. K. Suykens

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2008
76EEVanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Survival SVM: a practical scalable algorithm. ESANN 2008: 89-94
75EEMarco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens: Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation. ICANN (1) 2008: 175-184
74EECarlos Alzate, Johan A. K. Suykens: Sparse kernel models for spectral clustering using the incomplete Cholesky decomposition. IJCNN 2008: 3556-3563
73EECarlos Alzate, Johan A. K. Suykens: A regularized kernel CCA contrast function for ICA. Neural Networks 21(2-3): 170-181 (2008)
72EEFabian Ojeda, Johan A. K. Suykens, Bart De Moor: Low rank updated LS-SVM classifiers for fast variable selection. Neural Networks 21(2-3): 437-449 (2008)
2007
71EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Convex optimization for the design of learning machines. ESANN 2007: 193-204
70EEBen Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel: Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. ICANN (2) 2007: 139-148
69EEPeter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens: Multi-class kernel logistic regression: a fixed-size implementation. IJCNN 2007: 1756-1761
68EEFabian Ojeda, Johan A. K. Suykens, Bart De Moor: Variable selection by rank-one updates for least squares support vector machines. IJCNN 2007: 2283-2288
67EECarlos Alzate, Johan A. K. Suykens: ICA through an LS-SVM based Kernel CCA Measure for Independence. IJCNN 2007: 2920-2925
66EEKristiaan Pelckmans, Johan A. K. Suykens: Transductive Rademacher Complexities for Learning Over a Graph. MLG 2007
65EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: A Risk Minimization Principle for a Class of Parzen Estimators. NIPS 2007
64EEJan Luts, Arend Heerschap, Johan A. K. Suykens, Sabine Van Huffel: A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection. Artificial Intelligence in Medicine 40(2): 87-102 (2007)
63EEKristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Support and Quantile Tubes CoRR abs/cs/0703055: (2007)
62EEDániel Hillier, Serkan Günel, Johan A. K. Suykens, Joos Vandewalle: Partial Synchronization in oscillator Arrays with Asymmetric Coupling. I. J. Bifurcation and Chaos 17(11): 4177-4185 (2007)
61EEChuan Lu, Andy Devos, Johan A. K. Suykens, Carles Arús, Sabine Van Huffel: Bagging Linear Sparse Bayesian Learning Models for Variable Selection in Cancer Diagnosis. IEEE Transactions on Information Technology in Biomedicine 11(3): 338-347 (2007)
60EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: A Convex Approach to Validation-Based Learning of the Regularization Constant. IEEE Transactions on Neural Networks 18(3): 917-920 (2007)
59EELuc Hoegaerts, Lieven De Lathauwer, Ivan Goethals, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor: Efficiently updating and tracking the dominant kernel principal components. Neural Networks 20(2): 220-229 (2007)
2006
58EECarlos Alzate, Johan A. K. Suykens: A Weighted Kernel PCA Formulation with Out-of-Sample Extensions for Spectral Clustering Methods. IJCNN 2006: 138-144
57EEMustak E. Yalcin, Johan A. K. Suykens, Joos Vandewalle: Multi-scroll and hypercube attractors from Josephson junctions. ISCAS 2006
56EETony Van Gestel, Bart Baesens, Peter Van Dijcke, Joao Garcia, Johan A. K. Suykens, Jan Vanthienen: A process model to develop an internal rating system: Sovereign credit ratings. Decision Support Systems 42(2): 1131-1151 (2006)
55EETony Van Gestel, Bart Baesens, Johan A. K. Suykens, Dirk Van den Poel, Dirk-Emma Baestaens, Marleen Willekens: Bayesian kernel based classification for financial distress detection. European Journal of Operational Research 172(3): 979-1003 (2006)
54EEMustak E. Yalcin, Johan A. K. Suykens: Spatiotemporal Pattern Formation on the ACE16K CNN Chip. I. J. Bifurcation and Chaos 16(5): 1537-1546 (2006)
53EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods. Machine Learning 62(3): 217-252 (2006)
2005
52EENathalie Pochet, Frizo A. L. Janssens, Frank De Smet, Kathleen Marchal, Ignace Vergote, Johan A. K. Suykens, Bart De Moor: M@CBETH: Optimizing Clinical Microarray Classification. CSB Workshops 2005: 89-90
51EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Componentwise Support Vector Machines for Structure Detection. ICANN (2) 2005: 643-648
50EEMustak E. Yalcin, Johan A. K. Suykens, Joos Vandewalle: Spatiotemporal pattern formation in the ACE16k CNN chip. ISCAS (6) 2005: 5814-5817
49EEMarcelo Espinoza, Johan A. K. Suykens, Bart De Moor: Load Forecasting Using Fixed-Size Least Squares Support Vector Machines. IWANN 2005: 1018-1026
48EEB. Pluymers, L. Roobrouck, J. Buijs, Johan A. K. Suykens, Bart De Moor: Constrained linear MPC with time-varying terminal cost using convex combinations. Automatica 41(5): 831-837 (2005)
47EEIvan Goethals, Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Identification of MIMO Hammerstein models using least squares support vector machines. Automatica 41(7): 1263-1272 (2005)
46EENathalie Pochet, Frizo A. L. Janssens, Frank De Smet, Kathleen Marchal, Johan A. K. Suykens, Bart De Moor: M@CBETH: a microarray classification benchmarking tool. Bioinformatics 21(14): 3185-3186 (2005)
45EEKristiaan Pelckmans, Ivan Goethals, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Componentwise Least Squares Support Vector Machines CoRR abs/cs/0504086: (2005)
44EEKristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Handling missing values in support vector machine classifiers. Neural Networks 18(5-6): 684-692 (2005)
43EEKristiaan Pelckmans, Marcelo Espinoza, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Primal-Dual Monotone Kernel Regression. Neural Processing Letters 22(2): 171-182 (2005)
42EELuc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor: Subset based least squares subspace regression in RKHS. Neurocomputing 63: 293-323 (2005)
41EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Building sparse representations and structure determination on LS-SVM substrates. Neurocomputing 64: 137-159 (2005)
40EEKristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: The differogram: Non-parametric noise variance estimation and its use for model selection. Neurocomputing 69(1-3): 100-122 (2005)
2004
39EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Sparse LS-SVMs using additive regularization with a penalized validation criterion. ESANN 2004: 435-440
38EEKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs. ICONIP 2004: 1216-1222
37EELuc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor: A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines. ICONIP 2004: 1247-1253
36 Mustak E. Yalcin, Johan A. K. Suykens, Joos Vandewalle: A double scroll based true random bit generator. ISCAS (4) 2004: 581-584
35EETijl De Bie, Johan A. K. Suykens, Bart De Moor: Learning from General Label Constraints. SSPR/SPR 2004: 671-679
34EELukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, F. A. Howe, Carles Majós, A. Moreno-Torres, M. Van Der Graaf, Anne Rosemary Tate, Carles Arús, Sabine Van Huffel: Brain tumor classification based on long echo proton MRS signals. Artificial Intelligence in Medicine 31(1): 73-89 (2004)
33EENathalie Pochet, Frank De Smet, Johan A. K. Suykens, Bart De Moor: Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction. Bioinformatics 20(17): 3185-3195 (2004)
32EETony Van Gestel, Johan A. K. Suykens, Bart Baesens, Stijn Viaene, Jan Vanthienen, Guido Dedene, Bart De Moor, Joos Vandewalle: Benchmarking Least Squares Support Vector Machine Classifiers. Machine Learning 54(1): 5-32 (2004)
2003
31EEChuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Dirk Timmerman, Ignace Vergote: Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. AIME 2003: 219-228
30EELuc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor: Kernel PLS variants for regression. ESANN 2003: 200-208
29EEJohan A. K. Suykens, Mustak E. Yalcin, Joos Vandewalle: Coupled chaotic simulated annealing processes. ISCAS (3) 2003: 582-585
28EEChuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Ignace Vergote, Dirk Timmerman: Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. Artificial Intelligence in Medicine 28(3): 281-306 (2003)
2002
27 Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Sabine Van Huffel, Anne Rosemary Tate, Carles Majós, Carles Arús: The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals. ESANN 2002: 131-136
26 Lieveke Ameye, Chuan Lu, Lukas Lukas, Jos De Brabanter, Johan A. K. Suykens, Sabine Van Huffel, Hans Daniels, Gunnar Naulaers, Hugo Devlieger: Prediction of mental development of preterm newborns at birth time using LS-SVM. ESANN 2002: 167-172
25EEJos De Brabanter, Kristiaan Pelckmans, Johan A. K. Suykens, Joos Vandewalle: Robust Cross-Validation Score Function for Non-linear Function Estimation. ICANN 2002: 713-719
24EEBart Hamers, Johan A. K. Suykens, Bart De Moor: Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models. ICANN 2002: 720-726
23EEJohan A. K. Suykens, Joos Vandewalle, Bart De Moor: Intelligence and Cooperative Search by Coupled Local Minimizers CoRR cs.AI/0210030: (2002)
22EEMustak E. Yalcin, Johan A. K. Suykens, Joos Vandewalle, Serdar Özoguz: Families of scroll Grid attractors. I. J. Bifurcation and Chaos 12(1): 23-41 (2002)
21EETony Van Gestel, Johan A. K. Suykens, Gert R. G. Lanckriet, Annemie Lambrechts, Bart De Moor, Joos Vandewalle: Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis. Neural Computation 14(5): 1115-1147 (2002)
20 Tony Van Gestel, Johan A. K. Suykens, Gert R. G. Lanckriet, Annemie Lambrechts, Bart De Moor, Joos Vandewalle: Multiclass LS SVMs Moderated Outputs and Coding Decoding Schemes. Neural Processing Letters 15(1): 45-58 (2002)
19EEJohan A. K. Suykens, Jos De Brabanter, Lukas Lukas, Joos Vandewalle: Weighted least squares support vector machines: robustness and sparse approximation. Neurocomputing 48(1-4): 85-105 (2002)
2001
18EETony Van Gestel, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle: Automatic relevance determination for Least Squares Support Vector Machines classifiers. ESANN 2001: 13-18
17EETony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor, Joos Vandewalle: Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines. ICANN 2001: 384-389
16 Stijn Viaene, Bart Baesens, Tony Van Gestel, Johan A. K. Suykens, Dirk Van den Poel, Jan Vanthienen, Bart De Moor, Guido Dedene: Knowledge discovery in a direct marketing case using least squares support vector machines. Int. J. Intell. Syst. 16(9): 1023-1036 (2001)
15 Michel Duhoux, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle: Improved Long-Term Temperature Prediction by Chaining of Neural Networks. Int. J. Neural Syst. 11(1): 1-10 (2001)
14EEJohan A. K. Suykens, Joos Vandewalle, Bart De Moor: Optimal control by least squares support vector machines. Neural Networks 14(1): 23-35 (2001)
2000
13EEJohan A. K. Suykens, Joos Vandewalle: The K.U.Leuven competition data: a challenge for advanced neural network techniques. ESANN 2000: 299-304
12EEJohan A. K. Suykens, Lukas Lukas, Joos Vandewalle: Sparse least squares Support Vector Machine classifiers. ESANN 2000: 37-42
11EEBart Baesens, Stijn Viaene, Tony Van Gestel, Johan A. K. Suykens, Guido Dedene, Bart De Moor, Jan Vanthienen: An empirical assessment of kernel type performance for least squares support vector machine classifiers. KES 2000: 313-316
10EEStijn Viaene, Bart Baesens, Tony Van Gestel, Johan A. K. Suykens, Dirk Van den Poel, Jan Vanthienen, Bart De Moor, Guido Dedene: Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case. PKDD 2000: 657-664
1999
9EEMustak E. Yalcin, Johan A. K. Suykens, Joos Vandewalle: On the realization of n-scroll attractors. ISCAS (5) 1999: 483-486
8EEJohan A. K. Suykens, Joos Vandewalle: Training multilayer perceptron classifiers based on a modified support vector method. IEEE Transactions on Neural Networks 10(4): 907-911 (1999)
7 Johan A. K. Suykens, Joos Vandewalle: Least Squares Support Vector Machine Classifiers. Neural Processing Letters 9(3): 293-300 (1999)
1998
6EEJohan A. K. Suykens, Joos Vandewalle: Improved generalization ability of neurocontrollers by imposing NLq stability constraints. ESANN 1998: 99-104
5 Johan A. K. Suykens, Herman Verrelst, Joos Vandewalle: On-Line Learning Fokker-Planck Machine. Neural Processing Letters 7(2): 81-89 (1998)
1997
4EEJohan A. K. Suykens, Bart De Moor, Joos Vandewalle: NLq Theory: A Neural Control Framework with Global Asymptotic Stability Criteria. Neural Networks 10(4): 615-637 (1997)
1996
3 Johan A. K. Suykens, Philippe Lemmerling, W. Favoreel, Bart De Moor, M. Crepel, P. Briol: Modelling the Belgian Gas Consumption Using Neural Networks. Neural Processing Letters 4(3): 157-166 (1996)
1995
2 Johan A. K. Suykens, Joos Vandewalle: Generalized Cellular Neural Networks Represented in he NLq Framework. ISCAS 1995: 645-648
1994
1EEJohan A. K. Suykens, Bart De Moor, Joos Vandewalle: Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points. Neural Networks 7(5): 819-831 (1994)

Coauthor Index

1Carlos Alzate [58] [67] [73] [74]
2Lieveke Ameye [26]
3Carles Arús [27] [34] [61]
4Bart Baesens [10] [11] [16] [32] [55] [56]
5Dirk-Emma Baestaens [55]
6Vanya Van Belle [76]
7Tijl De Bie [35]
8Tom Bourne [70]
9Jos De Brabanter [17] [19] [25] [26] [40] [43] [44] [45] [63]
10P. Briol [3]
11J. Buijs [48]
12Ben Van Calster [70]
13George Condous [70]
14M. Crepel [3]
15Hans Daniels [26]
16Guido Dedene [10] [11] [16] [32]
17Hugo Devlieger [26]
18Andy Devos [27] [34] [61]
19Peter Van Dijcke [56]
20Michel Duhoux [15]
21Marcelo Espinoza [43] [49]
22W. Favoreel [3]
23Joao Garcia [56]
24Tony Van Gestel [10] [11] [16] [17] [18] [20] [21] [28] [31] [32] [55] [56]
25Ivan Goethals [45] [47] [59]
26M. Van Der Graaf [34]
27Serkan Günel [62]
28Bart Hamers [24]
29Arend Heerschap [64]
30Dániel Hillier [62]
31Luc Hoegaerts [30] [37] [42] [59]
32F. A. Howe [34]
33Sabine Van Huffel [26] [27] [28] [31] [34] [61] [64] [70] [76]
34Frizo A. L. Janssens [46] [52]
35Peter Karsmakers [69]
36Annemie Lambrechts [20] [21]
37Gert R. G. Lanckriet [20] [21]
38Lieven De Lathauwer [59]
39Philippe Lemmerling [3]
40Chuan Lu [26] [28] [31] [61]
41Lukas Lukas [12] [19] [26] [27] [34]
42Jan Luts [64] [70]
43Carles Majós [27] [34]
44Kathleen Marchal [46] [52]
45Bart De Moor [1] [3] [4] [10] [11] [14] [15] [16] [17] [18] [20] [21] [23] [24] [30] [32] [33] [35] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [51] [52] [53] [59] [60] [63] [65] [68] [71] [72]
46A. Moreno-Torres [34]
47Gunnar Naulaers [26]
48Fabian Ojeda [68] [72]
49Serdar Özoguz [22]
50Kristiaan Pelckmans [25] [38] [39] [40] [41] [43] [44] [45] [47] [51] [53] [60] [63] [65] [66] [69] [71] [75] [76]
51B. Pluymers [48]
52Nathalie Pochet [33] [46] [52]
53Dirk Van den Poel [10] [16] [55]
54L. Roobrouck [48]
55Marco Signoretto [75]
56Frank De Smet [33] [46] [52]
57Anne Rosemary Tate [27] [34]
58Dirk Timmerman [28] [31] [70]
59Joos Vandewalle [1] [2] [4] [5] [6] [7] [8] [9] [12] [13] [14] [15] [17] [18] [19] [20] [21] [22] [23] [25] [29] [30] [32] [36] [37] [42] [50] [57] [59] [62]
60Leentje Vanhamme [27] [34]
61Jan Vanthienen [10] [11] [16] [32] [56]
62Ignace Vergote [28] [31] [52]
63Herman Verrelst [5]
64Stijn Viaene [10] [11] [16] [32]
65Marleen Willekens [55]
66Mustak E. Yalcin [9] [22] [29] [36] [50] [54] [57]

Colors in the list of coauthors

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