L. Hoegaerts

Subset based least squares subspace regression in RKHS

L. Hoegaerts, Johan A. K. Suykens, Joos Vandewalle et al. · Neurocomputing · 2004 · 63 citations

Low-rank Approximation, Engineering, Reproducing Kernel Method +5

Efficiently updating and tracking the dominant kernel principal components

L. Hoegaerts, Lieven De Lathauwer, Ivan Goethals et al. · Neural Networks · 2007 · 57 citations

Machine Vision, Machine Learning, Data Science +8

A comparative study of ls-svm’s applied to the silver box identification problem

Marcelo Espinoza, Kristiaan Pelckmans, L. Hoegaerts et al. · IFAC Proceedings Volumes · 2004 · 31 citations

Support Vector Machine, Image Analysis, Machine Learning +11

Primal space sparse kernel partial least squares regression for large scale problems

L. Hoegaerts, Johan A. K. Suykens, Joos Vandewalle et al. · 2005 · 23 citations

Engineering, Machine Learning, Fixed-size Least Squares +19

Subspace intersection identification of Hammerstein-Wiener systems

Ivan Goethals, Kristiaan Pelckmans, L. Hoegaerts et al. · 2006 · 22 citations

Engineering, Regression Problem, Functional Analysis +16