Kris De Brabanter

16 papers A* 1B 3Journal 11Unranked 1
YearRankTypeTitle / Venue / Authors
2020 J jnl
Smoothed Nonparametric Derivative Estimation using Weighted Difference Quotients.
J. Mach. Learn. Res.
Yu Liu, Kris De Brabanter
2018 A* conf
Derivative Estimation in Random Design.
NeurIPS
Yu Liu, Kris De Brabanter
2017 J jnl
fourierin: An R package to compute Fourier integrals.
R J.
Guillermo Basulto-Elias, Alicia L. Carriquiry, Kris De Brabanter, Daniel J. Nordman
2016 J jnl
Wavelet Filter Design for Pavement Roughness Analysis.
Comput. Aided Civ. Infrastructure Eng.
Ahmad Alhasan, David J. White, Kris De Brabanter
2014 J jnl
New Bandwidth Selection Criterion for Kernel PCA: Approach to Dimensionality Reduction and Classification Problems.
BMC Bioinform.
Minta Thomas, Kris De Brabanter, Bart De Moor
2014 J jnl
Predicting breast cancer using an expression values weighted clinical classifier.
BMC Bioinform.
Minta Thomas, Kris De Brabanter, Johan A. K. Suykens, Bart De Moor
2013 J jnl
Derivative estimation with local polynomial fitting.
J. Mach. Learn. Res.
Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irène Gijbels
2012 J jnl
Confidence bands for least squares support vector machine classifiers: A regression approach.
Pattern Recognit.
Kris De Brabanter, Peter Karsmakers, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
2012 B conf
Deconvolution in nonparametric statistics.
ESANN
Kris De Brabanter, Bart De Moor
2012 B conf
Robustness of kernel based regression: Influence and weight functions.
IJCNN
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor
2011 J jnl
Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression.
IEEE Trans. Neural Networks
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
2011 J jnl
Kernel Regression in the Presence of Correlated Errors.
J. Mach. Learn. Res.
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
2011 B conf
Sparse LS-SVMs with L0 - norm minimization.
ESANN
Jorge López Lázaro, Kris De Brabanter, José R. Dorronsoro, Johan A. K. Suykens
2011 J jnl
Sparse conjugate directions pursuit with application to fixed-size kernel models.
Mach. Learn.
Peter Karsmakers, Kristiaan Pelckmans, Kris De Brabanter, Hugo Van hamme, Johan A. K. Suykens
2010 J jnl
Optimized fixed-size kernel models for large data sets.
Comput. Stat. Data Anal.
Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor
2009 — conf
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes.
ICANN (1)
Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor