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- Publications
- Influence

Least Squares Support Vector Machine Classifiers

- J. Suykens, J. Vandewalle
- Computer Science, Mathematics
- Neural Processing Letters
- 1 June 1999

In this letter we discuss a least squares version for support vector machine (SVM) classifiers. Due to equality type constraints in the formulation, the solution follows from solving a set of linear… Expand

Least Squares Support Vector Machines

- J. Suykens, T. V. Gestel, J. D. Brabanter, B. Moor, J. Vandewalle
- Computer Science
- 2002

Least Squares Support Vector Machines

- J. Suykens, T. V. Gestel, J. D. Brabanter, B. D. Moor, J. Vandewalle
- Computer Science
- 14 November 2002

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… Expand

Weighted least squares support vector machines: robustness and sparse approximation

- J. Suykens, J. D. Brabanter, L. Lukas, J. Vandewalle
- Computer Science, Mathematics
- Neurocomputing
- 1 October 2002

Abstract Least squares support vector machines (LS-SVM) is an SVM version which involves equality instead of inequality constraints and works with a least squares cost function. In this way, the… Expand

Benchmarking state-of-the-art classification algorithms for credit scoring

- Bart Baesens, T. V. Gestel, S. Viaene, M. Stepanova, J. Suykens, J. Vanthienen
- Computer Science
- J. Oper. Res. Soc.
- 1 June 2003

In this paper, we study the performance of various state-of-the-art classification algorithms applied to eight real-life credit scoring data sets. Some of the data sets originate from major Benelux… Expand

Benchmarking Least Squares Support Vector Machine Classifiers

- T. V. Gestel, J. Suykens, +5 authors J. Vandewalle
- Mathematics, Computer Science
- Machine Learning
- 2004

In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares… Expand

Sparse approximation using least squares support vector machines

- J. Suykens, L. Lukas, J. Vandewalle
- Mathematics, Computer Science
- IEEE International Symposium on Circuits and…
- 28 May 2000

In least squares support vector machines (LS-SVMs) for function estimation Vapnik's /spl epsiv/-insensitive loss function has been replaced by a cost function which corresponds to a form of ridge… Expand

Least squares support vector machine classifiers: a large scale algorithm

- J. Suykens, L. Lukas, P. Dooren, J. Vandewalle
- Computer Science
- 1999

Support vector machines (SVM's) have been introduced in literature as a method for pattern recognition and function estimation, within the framework of statistical learning theory and structural risk… Expand

Master-Slave Synchronization of Lur'e Systems with Time-Delay

- M. E. Yalçin, J. Suykens, J. Vandewalle
- Mathematics, Computer Science
- Int. J. Bifurc. Chaos
- 2001

In this paper time-delay effects on the master–slave synchronization scheme are investigated. Sufficient conditions for master–slave synchronization of Lur'e systems are presented for a known… Expand

Coupled Simulated Annealing

- S. X. D. Souza, J. Suykens, J. Vandewalle, D. Bollé
- Computer Science, Medicine
- IEEE Transactions on Systems, Man, and…
- 1 April 2010

We present a new class of methods for the global optimization of continuous variables based on simulated annealing (SA). The coupled SA (CSA) class is characterized by a set of parallel SA processes… Expand