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Sabine Van Huffel: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. 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. [Citation Graph (0, 0)][DBLP]
    AIME, 2003, pp:219-228 [Conf]
  2. Peter Antal, Herman Verrelst, Dirk Timmerman, Sabine Van Huffel, Bart De Moor, Ignace Vergote
    Bayesian Networks in Ovarian Cancer Diagnosis: Potentials and Limitations. [Citation Graph (0, 0)][DBLP]
    CBMS, 2000, pp:103-108 [Conf]
  3. 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. [Citation Graph (0, 0)][DBLP]
    ESANN, 2002, pp:167-172 [Conf]
  4. 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. [Citation Graph (0, 0)][DBLP]
    ESANN, 2002, pp:131-136 [Conf]
  5. 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. [Citation Graph (0, 0)][DBLP]
    IAT Workshops, 2006, pp:208-211 [Conf]
  6. Giansalvo Cirrincione, Sabine Van Huffel, Maurizio Cirrincione
    The GeTLS EXIN Neuron for Linear Regression. [Citation Graph (0, 0)][DBLP]
    IJCNN (6), 2000, pp:285-289 [Conf]
  7. Ivan Markovsky, Sabine Van Huffel
    On Weighted Structured Total Least Squares. [Citation Graph (0, 0)][DBLP]
    LSSC, 2005, pp:695-702 [Conf]
  8. Nicola Mastronardi, Paul Van Dooren, Sabine Van Huffel
    On the Stability of the Generalized Schur Algorithm. [Citation Graph (0, 0)][DBLP]
    NAA, 2000, pp:560-567 [Conf]
  9. 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. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2003, v:28, n:3, pp:281-306 [Journal]
  10. 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. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2004, v:31, n:1, pp:73-89 [Journal]
  11. Sabine Van Huffel, Haesun Park
    Parallel Tri- and Bi-Diagonalization of Bordered Bidiagonal Matrices. [Citation Graph (0, 0)][DBLP]
    Parallel Computing, 1994, v:20, n:8, pp:1107-1128 [Journal]
  12. Philippe Lemmerling, Leentje Vanhamme, Sabine Van Huffel, Bart De Moor
    IQML-like algorithms for solving structured total least squares problems: a unified view. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2001, v:81, n:9, pp:1935-1945 [Journal]
  13. Jean-Michel Papy, Lieven De Lathauwer, Sabine Van Huffel
    Common pole estimation in multi-channel exponential data modeling. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2006, v:86, n:4, pp:846-858 [Journal]
  14. M. Schuermans, Philippe Lemmerling, Lieven De Lathauwer, Sabine Van Huffel
    The use of total least squares data fitting in the shape-from-moments problem. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2006, v:86, n:5, pp:1109-1115 [Journal]
  15. Geert Morren, Philippe Lemmerling, Sabine Van Huffel
    Decimative subspace-based parameter estimation techniques. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2003, v:83, n:5, pp:1025-1033 [Journal]
  16. Kris Hermus, Werner Verhelst, Philippe Lemmerling, Patrick Wambacq, Sabine Van Huffel
    Perceptual audio modeling with exponentially damped sinusoids. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2005, v:85, n:1, pp:163-176 [Journal]
  17. Alexander Kukush, Ivan Markovsky, Sabine Van Huffel
    Consistent fundamental matrix estimation in a quadratic measurement error model arising in motion analysis. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2002, v:41, n:1, pp:3-18 [Journal]
  18. Alexander Kukush, Ivan Markovsky, Sabine Van Huffel
    Consistent estimation in an implicit quadratic measurement error model. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2004, v:47, n:1, pp:123-147 [Journal]
  19. Diana M. Sima, Sabine Van Huffel
    A class of template splines. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2006, v:50, n:12, pp:3486-3499 [Journal]
  20. Ivan Markovsky, Maria Luisa Rastello, Amedeo Premoli, Alexander Kukush, Sabine Van Huffel
    The element-wise weighted total least-squares problem. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2006, v:50, n:1, pp:181-209 [Journal]
  21. 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. [Citation Graph (0, 0)][DBLP]
    Computer Methods and Programs in Biomedicine, 2007, v:85, n:2, pp:129-137 [Journal]
  22. Juan Miguel García-Gómez, Montserrat Robles, Sabine Van Huffel, Alfons Juan-Císcar
    Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data. [Citation Graph (0, 0)][DBLP]
    IbPRIA (2), 2007, pp:266-273 [Conf]
  23. 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. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2007, pp:139-148 [Conf]
  24. M. S. H. Aung, Paulo J. G. Lisboa, Terence A. Etchells, A. C. Testa, Ben Van Calster, Sabine Van Huffel, L. Valentin, Dirk Timmerman
    Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. [Citation Graph (0, 0)][DBLP]
    ISNN (2), 2007, pp:1177-1186 [Conf]
  25. 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. [Citation Graph (0, 0)][DBLP]
    IWANN, 2007, pp:1012-1019 [Conf]
  26. Sabine Van Huffel, Ivan Markovsky, Richard J. Vaccaro, Torsten Söderström
    Total least squares and errors-in-variables modeling. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2007, v:87, n:10, pp:2281-2282 [Journal]
  27. Ivan Markovsky, Sabine Van Huffel
    Overview of total least-squares methods. [Citation Graph (0, 0)][DBLP]
    Signal Processing, 2007, v:87, n:10, pp:2283-2302 [Journal]

  28. Towards a Clinical Decision Support System for Pregnancies of Unknown Location. [Citation Graph (, )][DBLP]


  29. Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI. [Citation Graph (, )][DBLP]


  30. Survival SVM: a practical scalable algorithm. [Citation Graph (, )][DBLP]


  31. Multi-class classification of ovarian tumors. [Citation Graph (, )][DBLP]


  32. Imposing Independence Constraints in the CP Model. [Citation Graph (, )][DBLP]


  33. MINLIP: Efficient Learning of Transformation Models. [Citation Graph (, )][DBLP]


  34. Multi-class AUC metrics and weighted alternatives. [Citation Graph (, )][DBLP]


  35. Algorithm for imposing SOBI-type constraints on the CP model. [Citation Graph (, )][DBLP]


  36. Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints. [Citation Graph (, )][DBLP]


  37. HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis. [Citation Graph (, )][DBLP]


  38. A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection. [Citation Graph (, )][DBLP]


  39. An application of methods for the probabilistic three-class classification of pregnancies of unknown location. [Citation Graph (, )][DBLP]


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