Jos De Brabanter

Publication Activity (10 Years)

Years Active: 2001-2019
Publications (10 Years): 1

Top Topics

Partial Derivatives

Ridge Regression

Support Vector Machine Classifiers

Predictive Control

Top Venues

Pattern Recognit.

IEEE J. Biomed. Health Informatics

J. Mach. Learn. Res.

Publications

Philippe Saey, Steven De Wilde, Annemarie M. Kökösy, Jos Knockaert, Dimitri De Schuyter, Jos De Brabanter
Using code generated by MATLAB for the Mold Level Control System of a Continuous Slab Caster in ArcelorMittal Gent. ETFA (2019)
Jeroen Wyffels, Jos De Brabanter, Pieter Crombez, Piet Verhoeve, Bart Nauwelaers, Lieven De Strycker
Distributed, Signal Strength-Based Indoor Localization Algorithm for Use in Healthcare Environments. IEEE J. Biomed. Health Informatics 18 (6) (2014)
Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irène Gijbels
Derivative estimation with local polynomial fitting. J. Mach. Learn. Res. 14 (1) (2013)
Bart Huyck, Jos De Brabanter, Bart De Moor, Jan F. M. Van Impe, Filip Logist
Model predictive control of a pilot-scale distillation column using a programmable automation controller. ECC (2013)
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 Recognit. 45 (6) (2012)
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor
Robustness of kernel based regression: Influence and weight functions. IJCNN (2012)
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Kernel Regression in the Presence of Correlated Errors. J. Mach. Learn. Res. 12 (2011)
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 Trans. Neural Networks 22 (1) (2011)
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Optimized fixed-size kernel models for large data sets. Comput. Stat. Data Anal. 54 (6) (2010)
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)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Least conservative support and tolerance tubes. IEEE Trans. Inf. Theory 55 (8) (2009)
Filip Logist, Bart Huyck, Maarten Fabré, Maarten Verwerft, Bert Pluymers, Jos De Brabanter, Bart De Moor, Jan F. M. Van Impe
Identification and control of a pilot scale binary distillation column. ECC (2009)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Support and Quantile Tubes CoRR (2007)
Andy Devos, Niki Bergans, Tom Dresselaers, Jos De Brabanter, Diana Maria Sima, Leentje Vanhamme, Florent Vanstapel, Paul Van Hecke, Sabine Van Huffel
Model order selection for quantification of a multi-exponential magnetic resonance spectrum. EMBC (2006)
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) (2005)
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) (2005)
Kristiaan Pelckmans, Marcelo Espinoza, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Primal-Dual Monotone Kernel Regression. Neural Process. Lett. 22 (2) (2005)
Kristiaan Pelckmans, Ivan Goethals, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Componentwise Least Squares Support Vector Machines CoRR (2005)
Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
Variogram based noise variance estimation and its use in kernel based regression. NNSP (2003)
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) (2002)
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)
Jos De Brabanter, Kristiaan Pelckmans, Johan A. K. Suykens, Joos Vandewalle
Robust Cross-Validation Score Function for Non-linear Function Estimation. ICANN (2002)
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)