Search Results - "Suykens, J"

Benchmarking state-of-the-art classification algorithms for credit scoring by Baesens, B, Van Gestel, T, Viaene, S, Stepanova, M, Suykens, J, Vanthienen, J

“…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…”
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Optimal control by least squares support vector machines by Suykens, J.A.K., Vandewalle, J., De Moor, B.

“…Support vector machines have been very successful in pattern recognition and function estimation problems. In this paper we introduce the use of least squares…”
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Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization by Necoara, I., Suykens, J. A. K.

“…In this paper, we propose a distributed algorithm for solving large-scale separable convex problems using Lagrangian dual decomposition and the interior-point…”
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Application of a Smoothing Technique to Decomposition in Convex Optimization by Necoara, I., Suykens, J.

“…Dual decomposition is a powerful technique for deriving decomposition schemes for convex optimization problems with separable structure. Although the augmented…”
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Improved performance on high-dimensional survival data by application of Survival-SVM by Van Belle, V., Pelckmans, K., Van Huffel, S., Suykens, J. A. K.

“…Motivation: New application areas of survival analysis as for example based on micro-array expression data call for novel tools able to handle high-dimensional…”
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Optimized fixed-size kernel models for large data sets by De Brabanter, K., De Brabanter, J., Suykens, J.A.K., De Moor, B.

“…A modified active subset selection method based on quadratic Rényi entropy and a fast cross-validation for fixed-size least squares support vector machines is…”
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Extending Newton's law from nonlocal-in-time kinetic energy by Suykens, J.A.K.

“…We study a new equation of motion derived from a context of classical Newtonian mechanics by replacing the kinetic energy with a form of nonlocal-in-time…”
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Least squares support vector machine classifiers by SUYKENS, J. A. K, VANDEWALLE, J

“…In this letter we discuss a least squares version for support vector machine (SVM) classifiers. Due to equality type constraints in the formulation, the…”
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Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis by Van Gestel, T, Suykens, J A K, Lanckriet, G, Lambrechts, A, De Moor, B, Vandewalle, J

“…The Bayesian evidence framework has been successfully applied to the design of multilayer perceptrons (MLPs) in the work of MacKay. Nevertheless, the training…”
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Confidence bands for least squares support vector machine classifiers: A regression approach by De Brabanter, K., Karsmakers, P., De Brabanter, J., Suykens, J.A.K., De Moor, B.

“…This paper presents bias-corrected 100(1−α)% simultaneous confidence bands for least squares support vector machine classifiers based on a regression…”
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Efficiently updating and tracking the dominant kernel principal components by Hoegaerts, L., De Lathauwer, L., Goethals, I., Suykens, J.A.K., Vandewalle, J., De Moor, B.

“…The dominant set of eigenvectors of the symmetrical kernel Gram matrix is used in many important kernel methods (like e.g. kernel Principal Component Analysis,…”
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Sequentially activated groups in neural networks by Komarov, M. A, Osipov, G. V, Suykens, J. A. K

“…The internal neuronal dynamics, network configurations and coupling are influencing the output of neuronal networks through different external actions. One…”
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A support vector machine formulation to PCA analysis and its kernel version by Suykens, J.A.K., Van Gestel, T., Vandewalle, J., De Moor, B.

“…In this paper, we present a simple and straightforward primal-dual support vector machine formulation to the problem of principal component analysis (PCA) in…”
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Kernel Component Analysis Using an Epsilon-Insensitive Robust Loss Function by Alzate, C., Suykens, J.

“…Kernel principal component analysis (PCA) is a technique to perform feature extraction in a high-dimensional feature space, which is nonlinearly related to the…”
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Additive survival least-squares support vector machines by Van Belle, V., Pelckmans, K., Suykens, J. A. K., Van Huffel, S.

“…This work studies a new survival modeling technique based on least‐squares support vector machines. We propose the use of a least‐squares support vector…”
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Towards the detection of error-related potentials and its integration in the context of a P300 speller brain–computer interface by Combaz, A., Chumerin, N., Manyakov, N.V., Robben, A., Suykens, J.A.K., Van Hulle, M.M.

“…A P300 Speller is a brain–computer interface (BCI) that enables subjects to spell text on a computer screen by detecting P300 Event-Related Potentials in their…”
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Support vector machines versus logistic regression: improving prospective performance in clinical decision‐making by Pochet, N. L. M. M., Suykens, J. A. K.

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Financial time series prediction using least squares support vector machines within the evidence framework by Van Gestel, T., Suykens, J.A.K., Baestaens, D.-E., Lambrechts, A., Lanckriet, G., Vandaele, B., De Moor, B., Vandewalle, J.

“…The Bayesian evidence framework is applied in this paper to least squares support vector machine (LS-SVM) regression in order to infer nonlinear models for…”
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Preoperative diagnosis of ovarian tumors using Bayesian kernel‐based methods by Van Calster, B., Timmerman, D., Lu, C., Suykens, J. A. K., Valentin, L., Van Holsbeke, C., Amant, F., Vergote, I., Van Huffel, S.

“…Objectives To develop flexible classifiers that predict malignancy in adnexal masses using a large database from nine centers. Methods The database consisted…”
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Metastable states and transient activity in ensembles of excitatory and inhibitory elements by Komarov, M. A, Osipov, G. V, Suykens, J. A. K

“…Complex activity in biological neuronal networks can be represented as a sequential transition between complicated metastable states. From a dynamical systems…”
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