Search Results - "De Brabanter, J."

Weighted least squares support vector machines: robustness and sparse approximation by Suykens, J.A.K., De Brabanter, J., Lukas, L., Vandewalle, J.

“…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…”
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Monitoring the evolution of free and cysteinylated aldehydes from malt to fresh and forced aged beer by Bustillo Trueba, P., Jaskula-Goiris, B., Ditrych, M., Filipowska, W., De Brabanter, J., De Rouck, G., Aerts, G., De Cooman, L., De Clippeleer, J.

“…[Display omitted] •Free and cysteinylated aldehydes were monitored in malt, wort, fresh and aged beer.•Formation of cysteinylated aldehydes is found during…”
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Validation of an ultra-high-performance liquid chromatography-mass spectrometry method for the quantification of cysteinylated aldehydes and application to malt and beer samples by Bustillo Trueba, P., Jaskula-Goiris, B., De Clippeleer, J., Goiris, K., Praet, T., Sharma, U.K., Van der Eycken, E., Sanders, M.G., Vincken, J.-P., De Brabanter, J., De Rouck, G., Aerts, G., De Cooman, L.

“…•Validation of a methodology for the quantification of cysteinylated aldehydes by liquid–chromatography mass–spectrometry was obtained.•Cysteinylated aldehydes…”
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Color Doppler and gray‐scale ultrasound evaluation of the postpartum uterus by Van Den Bosch, T., Van Schoubroeck, D., Lu, C., De Brabanter, J., Van Huffel, S., Timmerman, D.

“…Objectives To evaluate the color Doppler and gray‐scale sonographic appearance of the uterus after pregnancy, with special attention to the occurrence of areas…”
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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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Ultrasonographic features of the endometrium and the ovaries in women on etonogestrel implant by Van Den Bosch, T., Donders, G. G. G., Riphagen, I., Debois, P., Ameye, L., De Brabanter, J., Van Huffel, S., Van Schoubroeck, D., Timmerman, D.

“…Objective To evaluate the ultrasound features of the endometrium and ovaries in women on etonogestrel implant, and to correlate these features with the…”
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Handling missing values in support vector machine classifiers by Pelckmans, K., De Brabanter, J., Suykens, J.A.K., De Moor, B.

“…This paper discusses the task of learning a classifier from observed data containing missing values amongst the inputs which are missing completely at random 1…”
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New models to predict depth of infiltration in endometrial carcinoma based on transvaginal sonography by De Smet, F., De Brabanter, J., Van den Bosch, T., Pochet, N., Amant, F., Van Holsbeke, C., Moerman, P., De Moor, B., Vergote, I., Timmerman, D.

“…Objectives Preoperative knowledge of the depth of myometrial infiltration is important in patients with endometrial carcinoma. This study aimed at assessing…”
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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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Least Conservative Support and Tolerance Tubes by Pelckmans, K., De Brabanter, J., Suykens, J.A.K., De Moor, B.

“…This paper studies a distribution-free estimator of the conditional support and tolerance intervals of a distributions underlying a set of paired independent…”
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Primal-dual monotone kernel regression by PELCKMANS, K, ESPINOZA, M, DE BRABANTER, J, SUYKENS, J. A. K, DE MOOR, B

“…This paper considers the estimation of monotone nonlinear regression functions based on Support Vector Machines (SVMs), Least Squares SVMs (LS-SVMs) and other…”
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The influence of hormone replacement therapy on the ultrasound features of the endometrium: a prospective study by Van den Bosch, T, Van Schoubroeck, D, Ameye, L, De Brabanter, J, Van Huffel, S, Timmerman, D

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Absence of correlation between risk factors for endometrial cancer and the presence of tamoxifen-associated endometrial polyps in postmenopausal patients with breast cancer by Timmerman, D, Deprest, J, Verbesselt, R, Moerman, P, De Brabanter, J, Vergote, I

“…In order to investigate the presence of established risk factors for endometrial carcinoma in postmenopausal patients with breast cancer and with…”
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Prognostic importance of degree of differentiation and cyst rupture in stage I invasive epithelial ovarian carcinoma by Vergote, Ignace, De Brabanter, Jos, Fyles, Anthony, Bertelsen, Kamma, Einhorn, Nina, Sevelda, Paul, Gore, Martin E, Kærn, Janne, Verrelst, Herman, Sjövall, Kjerstin, Timmerman, Dirk, Vandewalle, Joos, Van Gramberen, Marleen, Tropé, Claes G

“…Previous studies on prognostic factors in stage I invasive epithelial ovarian carcinoma have been too small for robust conclusions to be reached. We undertook…”
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Identification and control of a pilot scale binary distillation column by Logist, F., Huyck, B., Fabre, M., Verwerft, M., Pluymers, B., De Brabanter, J., De Moor, B., Van Impe, J.

“…This paper describes the design and implementation of a model predictive controller (MPC) for a pilot scale binary distillation column containing a mixture of…”
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Model order selection for quantification of a multi-exponential magnetic resonance spectrum by Devos, A., Bergans, N., Dresselaers, I., De Brabanter, J., Sima, D.M., Vanhamme, L., Vanstapel, F., Van Hecke, P., Van Huffel, S.

“…Magnetic resonance spectroscopic signals analyzed by time-domain models in order to retrieve estimates of the model parameters usually require prior knowledge…”
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The differogram: Non-parametric noise variance estimation and its use for model selection by Pelckmans, Kristiaan, De Brabanter, Jos, Suykens, Johan A.K., De Moor, Bart

“…Model-free estimates of the noise variance are important in model selection and setting tuning parameters. In this paper a data representation is discussed…”
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Least squares support vector machine regression for discriminant analysis by Van Gestel, T., Suykens, J.A.K., De Brabanter, J., De Moor, B., Vandewalle, J.

“…Support vector machine (SVM) classifiers aim at constructing a large margin classifier in the feature space, while a nonlinear decision boundary is obtained in…”
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Ultrasound assessment of endometrial thickness and endometrial polyps in women on hormonal replacement therapy by Van den Bosch, Thierry, Van Schoubroeck, Dominique, Ameye, Lieveke, De Brabanter, Jos, Van Huffel, Sabine, Timmerman, Dirk

“…Objective: This study was performed to evaluate the thickness and the sonographic features of the endometrium in postmenopausal women on hormone replacement…”
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Variogram based noise variance estimation and its use in kernel based regression by Pelckmans, K., De Brabanter, J., Suykens, J.A.K., De Moor, B.

“…Model-free estimates of the noise variance are important for doing model selection and setting tuning parameters. In this paper a data representation is…”
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