Jos De Brabanter

	2012
15		Kris De Brabanter, Peter Karsmakers, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Confidence bands for least squares support vector machine classifiers: A regression approach. Pattern Recognition 45(6): 2280-2287 (2012)
	2011
14		Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression. IEEE Transactions on Neural Networks 22(1): 110-120 (2011)
13		Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Kernel Regression in the Presence of Correlated Errors. Journal of Machine Learning Research 12: 1955-1976 (2011)
	2010
12		Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Optimized fixed-size kernel models for large data sets. Computational Statistics & Data Analysis 54(6): 1484-1504 (2010)
	2009
11		Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor: Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. ICANN (1) 2009: 100-110
10		Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Least conservative support and tolerance tubes. IEEE Transactions on Information Theory 55(8): 3799-3806 (2009)
	2007
9		Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor: Support and Quantile Tubes CoRR abs/cs/0703055: (2007)
	2005
8		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		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		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		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)
	2002
4		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
3		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
2		Johan 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
1		Tony 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

Coauthor Index

1	Lieveke Ameye	[4]
2	Kris De Brabanter	[11] [12] [13] [14] [15]
3	Hans Daniels	[4]
4	Michiel Debruyne	[11]
5	Hugo Devlieger	[4]
6	Marcelo Espinoza	[6]
7	Tony Van Gestel	[1]
8	Ivan Goethals	[8]
9	Mia Hubert	[11]
10	Sabine Van Huffel	[4]
11	Peter Karsmakers	[15]
12	Chuan Lu	[4]
13	Lukas Lukas	[2] [4]
14	Bart De Moor	[1] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15]
15	Gunnar Naulaers	[4]
16	Kristiaan Pelckmans	[3] [5] [6] [7] [8] [9] [10] [11]
17	Johan A. K. Suykens	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15]
18	Joos Vandewalle	[1] [2] [3]

Last update Sun May 27 04:04:01 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page