Kristiaan Pelckmans

2008
19	EE	Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Survival SVM: a practical scalable algorithm. ESANN 2008: 89-94
18	EE	Marco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens: Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation. ICANN (1) 2008: 175-184
2007
17	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Convex optimization for the design of learning machines. ESANN 2007: 193-204
16	EE	Peter Karsmakers, Kristiaan Pelckmans, Johan A. K. Suykens: Multi-class kernel logistic regression: a fixed-size implementation. IJCNN 2007: 1756-1761
15	EE	Kristiaan Pelckmans, Johan A. K. Suykens: Transductive Rademacher Complexities for Learning Over a Graph. MLG 2007
14	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: A Risk Minimization Principle for a Class of Parzen Estimators. NIPS 2007
13	EE	Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Support and Quantile Tubes CoRR abs/cs/0703055: (2007)
12	EE	Kristiaan 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)
2006
11	EE	Kristiaan 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
10	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Componentwise Support Vector Machines for Structure Detection. ICANN (2) 2005: 643-648
9	EE	Ivan 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)
8	EE	Kristiaan Pelckmans, Ivan Goethals, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Componentwise Least Squares Support Vector Machines CoRR abs/cs/0504086: (2005)
7	EE	Kristiaan 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)
6	EE	Kristiaan 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)
5	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Building sparse representations and structure determination on LS-SVM substrates. Neurocomputing 64: 137-159 (2005)
4	EE	Kristiaan 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
3	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Sparse LS-SVMs using additive regularization with a penalized validation criterion. ESANN 2004: 435-440
2	EE	Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor: Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs. ICONIP 2004: 1216-1222
2002
1	EE	Jos De Brabanter, Kristiaan Pelckmans, Johan A. K. Suykens, Joos Vandewalle: Robust Cross-Validation Score Function for Non-linear Function Estimation. ICANN 2002: 713-719

Coauthor Index

1	Vanya Van Belle	[19]
2	Jos De Brabanter	[1] [4] [6] [7] [8] [13]
3	Marcelo Espinoza	[6]
4	Ivan Goethals	[8] [9]
5	Sabine Van Huffel	[19]
6	Peter Karsmakers	[16]
7	Bart De Moor	[2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [17]
8	Marco Signoretto	[18]
9	Johan A. K. Suykens	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19]
10	Joos Vandewalle	[1]