J
Joos Vandewalle
Researcher at Katholieke Universiteit Leuven
Publications - 747
Citations - 42250
Joos Vandewalle is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Artificial neural network & Singular value decomposition. The author has an hindex of 73, co-authored 747 publications receiving 39621 citations. Previous affiliations of Joos Vandewalle include University of Virginia & Catholic University of Leuven.
Papers
More filters
Journal ArticleDOI
Least Squares Support Vector Machine Classifiers
TL;DR: A least squares version for support vector machine (SVM) classifiers that follows from solving a set of linear equations, instead of quadratic programming for classical SVM's.
Journal ArticleDOI
A Multilinear Singular Value Decomposition
TL;DR: There is a strong analogy between several properties of the matrix and the higher-order tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, first-order perturbation effects, etc., are analyzed.
Book
Least Squares Support Vector Machines
TL;DR: Support Vector Machines Basic Methods of Least Squares Support Vector Machines Bayesian Inference for LS-SVM Models Robustness Large Scale Problems LS- sVM for Unsupervised Learning LS- SVM for Recurrent Networks and Control.
Journal ArticleDOI
On the Best Rank-1 and Rank-( R 1 , R 2 ,. . ., R N ) Approximation of Higher-Order Tensors
TL;DR: A multilinear generalization of the best rank-R approximation problem for matrices, namely, the approximation of a given higher-order tensor, in an optimal least-squares sense, by a tensor that has prespecified column rank value, rowRank value, etc.
Book
The Total Least Squares Problem: Computational Aspects and Analysis
TL;DR: This paper presents a meta-analyses of the relationships between total least squares estimation and classical linear regression in Multicollinearity problems and some of the properties of these relationships are explained.