2008 | ||
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39 | EE | Ben Van Calster, Sabine Van Huffel, Dirk Timmerman, Emma Kirk, Tom Bourne, George Condous: Towards a Clinical Decision Support System for Pregnancies of Unknown Location. CBMS 2008: 581-583 |
38 | EE | Ben Van Calster, Dirk Timmerman, Antonia C. Testa, Lil Valentin, Sabine Van Huffel: Multi-class classification of ovarian tumors. ESANN 2008: 65-70 |
37 | EE | Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. Suykens, Sabine Van Huffel: Survival SVM: a practical scalable algorithm. ESANN 2008: 89-94 |
36 | EE | Ben Van Calster, Vanya Van Belle, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel: Multi-class AUC metrics and weighted alternatives. IJCNN 2008: 1390-1396 |
35 | EE | Maarten De Vos, Lieven De Lathauwer, Sabine Van Huffel: Algorithm for imposing SOBI-type constraints on the CP model. ISCAS 2008: 1344-1347 |
34 | EE | Ben Van Calster, Dirk Timmerman, Ian T. Nabney, Lil Valentin, Antonia C. Testa, Caroline Van Holsbeke, Ignace Vergote, Sabine Van Huffel: Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery. Neural Computing and Applications 17(5-6): 489-500 (2008) |
2007 | ||
33 | EE | Maarten De Vos, Lieven De Lathauwer, Sabine Van Huffel: Imposing Independence Constraints in the CP Model. ICA 2007: 33-40 |
32 | EE | Ben Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel: Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. ICANN (2) 2007: 139-148 |
31 | EE | M. S. Hane Aung, Paulo J. G. Lisboa, Terence A. Etchells, Antonia C. Testa, Ben Van Calster, Sabine Van Huffel, Lil Valentin, Dirk Timmerman: Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. ISNN (2) 2007: 1177-1186 |
30 | EE | Juan Miguel García-Gómez, Salvador Tortajada, Javier Vicente, Carlos Sáez, Xavier Castells, Jan Luts, Margarida Julià-Sapé, Alfons Juan-Císcar, Sabine Van Huffel, Anna Barcelo, Joaquín Ariño, Carles Arús, Montserrat Robles: Genomics and Metabolomics Research for Brain Tumour Diagnosis Based on Machine Learning. IWANN 2007: 1012-1019 |
29 | EE | Juan Miguel García-Gómez, Montserrat Robles, Sabine Van Huffel, Alfons Juan-Císcar: Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data. IbPRIA (2) 2007: 266-273 |
28 | EE | Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sabine Van Huffel: A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection. Artificial Intelligence in Medicine 40(2): 87-102 (2007) |
27 | EE | Sabine Van Huffel, Chi-Lun Cheng, Nicola Mastronardi, Chris Paige, Alexander Kukush: Total Least Squares and Errors-in-variables Modeling. Computational Statistics & Data Analysis 52(2): 1076-1079 (2007) |
26 | EE | Diana M. Sima, Sabine Van Huffel: Level choice in truncated total least squares. Computational Statistics & Data Analysis 52(2): 1103-1118 (2007) |
25 | EE | Alexander Kukush, Ivan Markovsky, Sabine Van Huffel: Estimation in a linear multivariate measurement error model with a change point in the data. Computational Statistics & Data Analysis 52(2): 1167-1182 (2007) |
24 | EE | B. De Neuter, Jan Luts, Leentje Vanhamme, Philippe Lemmerling, Sabine Van Huffel: Java-based framework for processing and displaying short-echo-time magnetic resonance spectroscopy signals. Computer Methods and Programs in Biomedicine 85(2): 129-137 (2007) |
23 | EE | Chuan Lu, Andy Devos, Johan A. K. Suykens, Carles Arús, Sabine Van Huffel: Bagging Linear Sparse Bayesian Learning Models for Variable Selection in Cancer Diagnosis. IEEE Transactions on Information Technology in Biomedicine 11(3): 338-347 (2007) |
22 | EE | Sabine Van Huffel, Ivan Markovsky, Richard J. Vaccaro, Torsten Söderström: Total least squares and errors-in-variables modeling. Signal Processing 87(10): 2281-2282 (2007) |
21 | EE | Ivan Markovsky, Sabine Van Huffel: Overview of total least-squares methods. Signal Processing 87(10): 2283-2302 (2007) |
2006 | ||
20 | EE | Carles Arús, Bernardo Celda, Srinandan Dasmahapatra, David Dupplaw, Horacio González-Vélez, Sabine Van Huffel, Paul H. Lewis, Magí Lluch i Ariet, Mariola Mier, Andrew Peet, Montserrat Robles: On the Design of a Web-Based Decision Support System for Brain Tumour Diagnosis Using Distributed Agents. IAT Workshops 2006: 208-211 |
19 | EE | Ivan Markovsky, Maria Luisa Rastello, Amedeo Premoli, Alexander Kukush, Sabine Van Huffel: The element-wise weighted total least-squares problem. Computational Statistics & Data Analysis 50(1): 181-209 (2006) |
18 | EE | Diana M. Sima, Sabine Van Huffel: A class of template splines. Computational Statistics & Data Analysis 50(12): 3486-3499 (2006) |
17 | EE | Jean-Michel Papy, Lieven De Lathauwer, Sabine Van Huffel: Common pole estimation in multi-channel exponential data modeling. Signal Processing 86(4): 846-858 (2006) |
16 | EE | M. Schuermans, Philippe Lemmerling, Lieven De Lathauwer, Sabine Van Huffel: The use of total least squares data fitting in the shape-from-moments problem. Signal Processing 86(5): 1109-1115 (2006) |
2005 | ||
15 | EE | Ivan Markovsky, Sabine Van Huffel: On Weighted Structured Total Least Squares. LSSC 2005: 695-702 |
14 | EE | Kris Hermus, Werner Verhelst, Philippe Lemmerling, Patrick Wambacq, Sabine Van Huffel: Perceptual audio modeling with exponentially damped sinusoids. Signal Processing 85(1): 163-176 (2005) |
2004 | ||
13 | EE | Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, F. A. Howe, Carles Majós, A. Moreno-Torres, M. Van Der Graaf, Anne Rosemary Tate, Carles Arús, Sabine Van Huffel: Brain tumor classification based on long echo proton MRS signals. Artificial Intelligence in Medicine 31(1): 73-89 (2004) |
12 | EE | Alexander Kukush, Ivan Markovsky, Sabine Van Huffel: Consistent estimation in an implicit quadratic measurement error model. Computational Statistics & Data Analysis 47(1): 123-147 (2004) |
2003 | ||
11 | EE | Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Dirk Timmerman, Ignace Vergote: Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines. AIME 2003: 219-228 |
10 | EE | Chuan Lu, Tony Van Gestel, Johan A. K. Suykens, Sabine Van Huffel, Ignace Vergote, Dirk Timmerman: Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines. Artificial Intelligence in Medicine 28(3): 281-306 (2003) |
9 | EE | Geert Morren, Philippe Lemmerling, Sabine Van Huffel: Decimative subspace-based parameter estimation techniques. Signal Processing 83(5): 1025-1033 (2003) |
2002 | ||
8 | Lukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Sabine Van Huffel, Anne Rosemary Tate, Carles Majós, Carles Arús: The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals. ESANN 2002: 131-136 | |
7 | Lieveke Ameye, Chuan Lu, Lukas Lukas, Jos De Brabanter, Johan A. K. Suykens, Sabine Van Huffel, Hans Daniels, Gunnar Naulaers, Hugo Devlieger: Prediction of mental development of preterm newborns at birth time using LS-SVM. ESANN 2002: 167-172 | |
6 | EE | Alexander Kukush, Ivan Markovsky, Sabine Van Huffel: Consistent fundamental matrix estimation in a quadratic measurement error model arising in motion analysis. Computational Statistics & Data Analysis 41(1): 3-18 (2002) |
2001 | ||
5 | EE | Philippe Lemmerling, Leentje Vanhamme, Sabine Van Huffel, Bart De Moor: IQML-like algorithms for solving structured total least squares problems: a unified view. Signal Processing 81(9): 1935-1945 (2001) |
2000 | ||
4 | EE | Peter Antal, Herman Verrelst, Dirk Timmerman, Sabine Van Huffel, Bart De Moor, Ignace Vergote: Bayesian Networks in Ovarian Cancer Diagnosis: Potentials and Limitations. CBMS 2000: 103-108 |
3 | EE | Giansalvo Cirrincione, Sabine Van Huffel, Maurizio Cirrincione: The GeTLS EXIN Neuron for Linear Regression. IJCNN (6) 2000: 285-289 |
2 | EE | Nicola Mastronardi, Paul Van Dooren, Sabine Van Huffel: On the Stability of the Generalized Schur Algorithm. NAA 2000: 560-567 |
1994 | ||
1 | Sabine Van Huffel, Haesun Park: Parallel Tri- and Bi-Diagonalization of Bordered Bidiagonal Matrices. Parallel Computing 20(8): 1107-1128 (1994) |