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ORCIDBart De Moor
B. L. R. De Moor
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- affiliation: Catholic University of Leuven, Belgium
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2020 – today
- 2024
[j179]Lukas Vanpoucke
, Bart De Moor:
Constructing Multidimensional Difference Equations From a State-Space Representation Using the Generalized Cayley-Hamilton Theorem. IEEE Control. Syst. Lett. 8: 2259-2264 (2024)- [j178]Lyse Naomi Wamba Momo, Nyalleng Moorosi, Elaine O. Nsoesie, Frank E. Rademakers, Bart De Moor:
Length of stay prediction for hospital management using domain adaptation. Eng. Appl. Artif. Intell. 133: 108088 (2024) - [j177]Melanie Schoutteten, Lucas Lindeboom, Hélène De Cannière, Zoë Pieters, Liesbeth Bruckers, Astrid D. H. Brys, Patrick van der Heijden, Bart De Moor, Jacques Peeters, Chris Van Hoof, Willemijn Groenendaal, Jeroen P. Kooman, Pieter M. Vandervoort:
The Feasibility of Semi-Continuous and Multi-Frequency Thoracic Bioimpedance Measurements by a Wearable Device during Fluid Changes in Hemodialysis Patients. Sensors 24(6): 1890 (2024) - [c160]Sibren Lagauw, Lukas Vanpoucke, Bart De Moor:
Exact Characterization of the Global Optima of Least Squares Realization of Autonomous LTI Models as a Multiparameter Eigenvalue Problem. ECC 2024: 3446-3451 - 2023
- [j176]Christof Vermeersch, Bart De Moor:
Two Double Recursive Block Macaulay Matrix Algorithms to Solve Multiparameter Eigenvalue Problems. IEEE Control. Syst. Lett. 7: 319-324 (2023) - [j175]Sibren Lagauw, Oscar Mauricio Agudelo, Bart De Moor:
Globally Optimal SISO H2-Norm Model Reduction Using Walsh's Theorem. IEEE Control. Syst. Lett. 7: 1670-1675 (2023) - [j174]Arun Pandey, Hannes De Meulemeester, Bart De Moor, Johan A. K. Suykens:
Multi-view kernel PCA for time series forecasting. Neurocomputing 554: 126639 (2023) - [j173]Christof Vermeersch, Bart De Moor:
Recursive Algorithms to Update a Numerical Basis Matrix of the Null Space of the Block Row, (Banded) Block Toeplitz, and Block Macaulay Matrix. SIAM J. Sci. Comput. 45(2): 596- (2023) - [j172]Konstantinos Theodorakos, Oscar Mauricio Agudelo, Joachim Schreurs, Johan A. K. Suykens, Bart De Moor:
Island Transpeciation: A Co-Evolutionary Neural Architecture Search, Applied to Country-Scale Air-Quality Forecasting. IEEE Trans. Evol. Comput. 27(4): 878-892 (2023) - [j171]Lola Botman, Jonas Soenen, Konstantinos Theodorakos, Aras Yurtman, Jessa Bekker, Koen Vanthournout, Hendrik Blockeel, Bart De Moor, Jesus Lago:
A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households. IEEE Trans. Smart Grid 14(1): 757-768 (2023) - [c159]Christof Vermeersch, Sibren Lagauw, Bart De Moor:
Multivariate Polynomial Optimization in Complex Variables Is a (Rectangular) Multiparameter Eigenvalue Problem. CDC 2023: 7305-7311 - [c158]Vincent Scheltjens, Lyse Naomi Wamba Momo, Wouter Verbeke, Bart De Moor:
Client Recruitment for Federated Learning in ICU Length of Stay Prediction. e-Science 2023: 1-9 - [c157]Giulia Rinaldi, Fernando Crema Garcia, Oscar Mauricio Agudelo, Thijs Becker, Koen Vanthournout, Willem Mestdagh, Bart De Moor:
A Framework for a Data Quality Module in Decision Support Systems: An Application with Smart Grid Time Series. ICEIS (1) 2023: 443-452 - [i22]Arun Pandey, Hannes De Meulemeester, Bart De Moor, Johan A. K. Suykens:
Multi-view Kernel PCA for Time series Forecasting. CoRR abs/2301.09811 (2023) - [i21]Vincent Scheltjens, Lyse Naomi Wamba Momo, Wouter Verbeke, Bart De Moor:
Client Recruitment for Federated Learning in ICU Length of Stay Prediction. CoRR abs/2304.14663 (2023) - [i20]Sonny Achten, Arun Pandey, Hannes De Meulemeester, Bart De Moor, Johan A. K. Suykens:
Duality in Multi-View Restricted Kernel Machines. CoRR abs/2305.17251 (2023) - [i19]Lyse Naomi Wamba Momo, Nyalleng Moorosi, Elaine O. Nsoesie, Frank E. Rademakers, Bart De Moor:
Length of Stay prediction for Hospital Management using Domain Adaptation. CoRR abs/2306.16823 (2023) - 2022
- [j170]Oliver Lauwers, Christof Vermeersch, Bart De Moor:
Cepstral identification of autoregressive systems. Autom. 139: 110214 (2022) - [j169]Thibaut Vaulet, Maya Al-Memar, Hanine Fourie, Shabnam Bobdiwala, Srdjan Saso, Maria Pipi, Catriona Stalder, Phillip R. Bennett, Dirk Timmerman, Tom Bourne, Bart De Moor:
Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy. Comput. Methods Programs Biomed. 213: 106520 (2022) - [c156]Arun Pandey, Hannes De Meulemeester, Henri De Plaen, Bart De Moor, Johan A. K. Suykens:
Recurrent Restricted Kernel Machines for Time-series Forecasting. ESANN 2022 - 2021
- [j168]Xi Shi, Gorana Nikolic, Gorka Epelde, Mónica Arrúe, Joseba Bidaurrazaga Van-Dierdonck, Roberto Bilbao, Bart De Moor:
An ensemble-based feature selection framework to select risk factors of childhood obesity for policy decision making. BMC Medical Informatics Decis. Mak. 21(1): 222 (2021) - [j167]Xi Shi, Charlotte Prins, Gijs Van Pottelbergh, Pavlos Mamouris, Bert Vaes, Bart De Moor:
An automated data cleaning method for Electronic Health Records by incorporating clinical knowledge. BMC Medical Informatics Decis. Mak. 21(1): 267 (2021) - [c155]Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens:
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks. LOD 2021: 466-480 - [c154]Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens:
The Bures Metric for Generative Adversarial Networks. ECML/PKDD (2) 2021: 52-66 - [i18]Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens:
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks. CoRR abs/2104.02373 (2021) - 2020
- [j166]João Pita Costa, Marko Grobelnik, Flavio Fuart, Luka Stopar, Gorka Epelde, Scott Fischaber, Piotr Poliwoda, Debbie Rankin, Jonathan G. Wallace, Michaela M. Black, Raymond R. Bond, Maurice D. Mulvenna, Dale Weston, Paul Carlin, Roberto Bilbao, Gorana Nikolic, Xi Shi, Bart De Moor, Minna Pikkarainen, Jarmo Pääkkönen, Anthony Staines, Regina Connolly, Paul Davis:
Meaningful Big Data Integration for a Global COVID-19 Strategy. IEEE Comput. Intell. Mag. 15(4): 51-61 (2020) - [j165]Bart De Moor:
Least squares optimal realisation of autonomous LTI systems is an eigenvalue problem. Commun. Inf. Syst. 20(2): 163-207 (2020) - [j164]Gorka Epelde, Andoni Beristain, Roberto Álvarez, Mónica Arrúe, Iker Ezkerra, Oihana Belar, Roberto Bilbao, Gorana Nikolic, Xi Shi, Bart De Moor, Maurice D. Mulvenna:
Quality of data measurements in the big data era: Lessons learned from MIDAS project. IEEE Instrum. Meas. Mag. 23(7): 18-24 (2020) - [c153]Hannes De Meulemeester, Bart De Moor:
Unsupervised Embeddings for Categorical Variables. IJCNN 2020: 1-8 - [i17]Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens:
The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks. CoRR abs/2006.09096 (2020)
2010 – 2019
- 2019
- [j163]Christof Vermeersch, Bart De Moor:
Globally Optimal Least-Squares ARMA Model Identification is an Eigenvalue Problem. IEEE Control. Syst. Lett. 3(4): 1062-1067 (2019) - [c152]Bart De Moor:
Least squares realization of LTI models is an eigenvalue problem. ECC 2019: 2270-2275 - 2018
- [j162]Oliver Lauwers, Oscar Mauricio Agudelo, Bart De Moor:
A Multiple-Input Multiple-Output Cepstrum. IEEE Control. Syst. Lett. 2(2): 272-277 (2018) - [j161]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional realisation theory and polynomial system solving. Int. J. Control 91(12): 2692-2704 (2018) - [c151]Bob Vergauwen, Oscar Mauricio Agudelo, Bart De Moor:
Order estimation of two dimensional systems based on rank decisions. CDC 2018: 1451-1456 - [c150]Bart De Moor, Yasamin Mostofi, Maryam Kamgarpour, Zdenko Kovacic, Maja Cepanec, Airlie Chapman, Mehran Mesbahi:
Plenary Lectures. MED 2018 - [i16]Oliver Lauwers, Oscar Mauricio Agudelo, Bart De Moor:
A Multiple-Input Multiple-Output Cepstrum. CoRR abs/1803.03080 (2018) - [i15]Oliver Lauwers, Bart De Moor:
Applicability and interpretation of the deterministic weighted cepstral distance. CoRR abs/1803.03104 (2018) - [i14]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional Realization Theory and Polynomial System Solving. CoRR abs/1805.02253 (2018) - 2017
- [j160]Oliver Lauwers, Bart De Moor:
A Time Series Distance Measure for Efficient Clustering of Input/Output Signals by Their Underlying Dynamics. IEEE Control. Syst. Lett. 1(2): 286-291 (2017) - [c149]Bob Vergauwen, Oscar Mauricio Agudelo, Raj Thilak Rajan, Frank J. Pasveer, Bart De Moor:
Data-driven modeling techniques for indoor CO2 estimation. IEEE SENSORS 2017: 1-3 - [i13]Oliver Lauwers, Bart De Moor:
A time series distance measure for efficient clustering of input output signals by their underlying dynamics. CoRR abs/1703.01923 (2017) - 2015
- [j159]Dusan Popovic, Alejandro Sifrim, Jesse Davis, Yves Moreau, Bart De Moor:
Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case. BMC Bioinform. 16(S-4): S2 (2015) - [j158]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
A robust ensemble approach to learn from positive and unlabeled data using SVM base models. Neurocomputing 160: 73-84 (2015) - [c148]Antoine Vandermeersch, Bart De Moor:
A SVD approach to multivariate polynomial optimization problems. CDC 2015: 7232-7237 - [c147]Mandar Chandorkar, Raghvendra Mall, Oliver Lauwers, Johan A. K. Suykens, Bart De Moor:
Fixed-Size Least Squares Support Vector Machines: Scala Implementation for Large Scale Classification. SSCI 2015: 522-528 - [c146]Dusan Popovic, Jesse Davis, Alejandro Sifrim, Bart De Moor:
A Note on the Evaluation of Mutation Prioritization Algorithms. SSCI 2015: 1351-1357 - [i12]Marc Claesen, Bart De Moor:
Hyperparameter Search in Machine Learning. CoRR abs/1502.02127 (2015) - [i11]Marc Claesen, Jesse Davis, Frank De Smet, Bart De Moor:
Assessing binary classifiers using only positive and unlabeled data. CoRR abs/1504.06837 (2015) - [i10]Marc Claesen, Frank De Smet, Pieter Gillard, Chantal Mathieu, Bart De Moor:
Building Classifiers to Predict the Start of Glucose-Lowering Pharmacotherapy Using Belgian Health Expenditure Data. CoRR abs/1504.07389 (2015) - 2014
- [j157]Minta Thomas, Kris De Brabanter, Bart De Moor:
New Bandwidth Selection Criterion for Kernel PCA: Approach to Dimensionality Reduction and Classification Problems. BMC Bioinform. 15: 137 (2014) - [j156]Minta Thomas, Kris De Brabanter, Johan A. K. Suykens, Bart De Moor:
Predicting breast cancer using an expression values weighted clinical classifier. BMC Bioinform. 15: 6603 (2014) - [j155]Rocco Langone, Oscar Mauricio Agudelo, Bart De Moor, Johan A. K. Suykens:
Incremental kernel spectral clustering for online learning of non-stationary data. Neurocomputing 139: 246-260 (2014) - [j154]Kim Batselier, Philippe Dreesen, Bart De Moor:
A fast recursive orthogonalization scheme for the Macaulay matrix. J. Comput. Appl. Math. 267: 20-32 (2014) - [j153]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
EnsembleSVM: a library for ensemble learning using support vector machines. J. Mach. Learn. Res. 15(1): 141-145 (2014) - [j152]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Canonical Decomposition of Cnd and Numerical Gröbner and Border Bases. SIAM J. Matrix Anal. Appl. 35(4): 1242-1264 (2014) - [j151]Minta Thomas, Anneleen Daemen, Bart De Moor:
Maximum Likelihood Estimation ofGEVD: Applications in Bioinformatics. IEEE ACM Trans. Comput. Biol. Bioinform. 11(4): 673-680 (2014) - [c145]Dusan Popovic, Charalampos N. Moschopoulos, Ryo Sakai, Alejandro Sifrim, Jan Aerts, Yves Moreau, Bart De Moor:
A Self-Tuning Genetic Algorithm with Applications in Biomarker Discovery. CBMS 2014: 233-238 - [c144]Charalampos N. Moschopoulos, Dusan Popovic, Rocco Langone, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Gene interaction networks boost genetic algorithm performance in biomarker discovery. MCDM 2014: 144-149 - [i9]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models. CoRR abs/1402.3144 (2014) - [i8]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
Fast Prediction with SVM Models Containing RBF Kernels. CoRR abs/1403.0736 (2014) - [i7]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines. CoRR abs/1403.0745 (2014) - [i6]Marc Claesen, Jaak Simm, Dusan Popovic, Yves Moreau, Bart De Moor:
Easy Hyperparameter Search Using Optunity. CoRR abs/1412.1114 (2014) - 2013
- [j150]Adeshola A. Adefioye, Xinhai Liu, Bart De Moor:
Multi-view spectral clustering and its chemical application. Int. J. Comput. Biol. Drug Des. 6(1/2): 32-49 (2013) - [j149]Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irène Gijbels:
Derivative estimation with local polynomial fitting. J. Mach. Learn. Res. 14(1): 281-301 (2013) - [j148]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Geometry of Multivariate Polynomial Division and Elimination. SIAM J. Matrix Anal. Appl. 34(1): 102-125 (2013) - [j147]Diana Ugryumova, Gerd Vandersteen, Bart Huyck, Filip Logist, Jan F. M. Van Impe, Bart De Moor:
Identification of a Noninsulated Distillation Column From Transient Response Data. IEEE Trans. Instrum. Meas. 62(5): 1382-1391 (2013) - [j146]Xinhai Liu, Shuiwang Ji, Wolfgang Glänzel, Bart De Moor:
Multiview Partitioning via Tensor Methods. IEEE Trans. Knowl. Data Eng. 25(5): 1056-1069 (2013) - [c143]Dusan Popovic, Alejandro Sifrim, Yves Moreau, Bart De Moor:
eXtasy simplified-towards opening the black box. BIBM 2013: 24-28 - [c142]Charalampos N. Moschopoulos, Dusan Popovic, Alejandro Sifrim, Grigorios N. Beligiannis, Bart De Moor, Yves Moreau:
A Genetic Algorithm for Pancreatic Cancer Diagnosis. EANN (2) 2013: 222-230 - [c141]Dusan Popovic, Alejandro Sifrim, Charalampos N. Moschopoulos, Yves Moreau, Bart De Moor:
A Hybrid Approach to Feature Ranking for Microarray Data Classification. EANN (2) 2013: 241-248 - [c140]Bart Huyck, Jos De Brabanter, Bart De Moor, Jan F. M. Van Impe, Filip Logist:
Model predictive control of a pilot-scale distillation column using a programmable automation controller. ECC 2013: 1053-1058 - 2012
- [j145]Anneleen Daemen, Dirk Timmerman, Thierry Van den Bosch, Cecilia Bottomley, Emma Kirk, Caroline Van Holsbeke, Lil Valentin, Tom Bourne, Bart De Moor:
Improved modeling of clinical data with kernel methods. Artif. Intell. Medicine 54(2): 103-114 (2012) - [j144]Ernesto Iacucci, Léon-Charles Tranchevent, Dusan Popovic, Georgios A. Pavlopoulos, Bart De Moor, Reinhard Schneider, Yves Moreau:
ReLiance: a machine learning and literature-based prioritization of receptor - ligand pairings. Bioinform. 28(18): 569-574 (2012) - [j143]Daniela Börnigen, Léon-Charles Tranchevent, Francisco Bonachela Capdevila, Koenraad Devriendt, Bart De Moor, Patrick De Causmaecker, Yves Moreau:
An unbiased evaluation of gene prioritization tools. Bioinform. 28(23): 3081-3088 (2012) - [j142]Ernesto Iacucci, Léon-Charles Tranchevent, Dusan Popovic, Georgios A. Pavlopoulos, Bart De Moor, Reinhard Schneider, Yves Moreau:
A bioinformatics e-dating story: computational prediction and prioritization of receptor-ligand pairs. BMC Bioinform. 13(S-18): A7 (2012) - [j141]Shi Yu, Léon-Charles Tranchevent, Xinhai Liu, Wolfgang Glänzel, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Optimized Data Fusion for Kernel k-Means Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 34(5): 1031-1039 (2012) - [j140]Kris De Brabanter, Peter Karsmakers, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Confidence bands for least squares support vector machine classifiers: A regression approach. Pattern Recognit. 45(6): 2280-2287 (2012) - [j139]Xinhai Liu, Wolfgang Glänzel, Bart De Moor:
Optimal and hierarchical clustering of large-scale hybrid networks for scientific mapping. Scientometrics 91(2): 473-493 (2012) - [c139]Maarten Breckpot, Oscar Mauricio Agudelo, Bart De Moor:
Model Predictive Control applied to a river system with two reaches. CDC 2012: 4549-4554 - [c138]Kim Batselier, Philippe Dreesen, Bart De Moor:
maximum likelihood estimation and polynomial system solving. ESANN 2012 - [c137]Kris De Brabanter, Bart De Moor:
Deconvolution in nonparametric statistics. ESANN 2012 - [c136]Philippe Dreesen, Kim Batselier, Bart De Moor:
Weighted/Structured Total Least Squares problems and polynomial system solving. ESANN 2012 - [c135]Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Joint Regression and Linear Combination of Time Series for Optimal Prediction. ESANN 2012 - [c134]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Robustness of kernel based regression: Influence and weight functions. IJCNN 2012: 1-8 - [c133]Dusan Popovic, Alejandro Sifrim, Georgios A. Pavlopoulos, Yves Moreau, Bart De Moor:
A Simple Genetic Algorithm for Biomarker Mining. PRIB 2012: 222-232 - [c132]Ernesto Iacucci, Dusan Popovic, Georgios A. Pavlopoulos, Léon-Charles Tranchevent, Marijke Bauters, Bart De Moor, Yves Moreau:
Towards Better Prioritization of Epigenetically Modified DNA Regions. SETN 2012: 270-277 - 2011
- [b3]Shi Yu, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Kernel-based Data Fusion for Machine Learning - Methods and Applications in Bioinformatics and Text Mining. Studies in Computational Intelligence 345, Springer 2011, ISBN 978-3-642-19405-4, pp. 1-208 - [j138]Léon-Charles Tranchevent, Francisco Bonachela Capdevila, Daniela Nitsch, Bart De Moor, Patrick De Causmaecker, Yves Moreau:
A guide to web tools to prioritize candidate genes. Briefings Bioinform. 12(1): 22-32 (2011) - [j137]Shi Yu, Xinhai Liu, Léon-Charles Tranchevent, Wolfgang Glänzel, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Optimized data fusion for K-means Laplacian clustering. Bioinform. 27(1): 118-126 (2011) - [j136]Ernesto Iacucci, Fabian Ojeda, Bart De Moor, Yves Moreau:
Predicting Receptor-Ligand Pairs through Kernel Learning. BMC Bioinform. 12: 336 (2011) - [j135]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Kernel Regression in the Presence of Correlated Errors. J. Mach. Learn. Res. 12: 1955-1976 (2011) - [j134]Xinhai Liu, Wolfgang Glänzel, Bart De Moor:
Hybrid clustering of multi-view data via Tucker-2 model and its application. Scientometrics 88(3): 819-839 (2011) - [j133]Marco Signoretto, Raf Van de Plas, Bart De Moor, Johan A. K. Suykens:
Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data. IEEE Signal Process. Lett. 18(7): 403-406 (2011) - [j132]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression. IEEE Trans. Neural Networks 22(1): 110-120 (2011) - [c131]Oscar Mauricio Agudelo, Oscar Barrero, Viaene Peter, Bart De Moor:
Assimilation of ozone measurements in the air quality model AURORA by using the Ensemble Kalman Filter. CDC/ECC 2011: 4430-4435 - 2010
- [j131]Shi Yu, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Gene prioritization and clustering by multi-view text mining. BMC Bioinform. 11: 28 (2010) - [j130]Shi Yu, Tillmann Falck, Anneleen Daemen, Léon-Charles Tranchevent, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
L2-norm multiple kernel learning and its application to biomedical data fusion. BMC Bioinform. 11: 309 (2010) - [j129]Daniela Nitsch, Joana P. Gonçalves, Fabian Ojeda, Bart De Moor, Yves Moreau:
Candidate gene prioritization by network analysis of differential expression using machine learning approaches. BMC Bioinform. 11: 460 (2010) - [j128]Julian Bonilla Alarcon, Moritz Diehl, Filip Logist, Bart De Moor, Jan F. M. Van Impe:
An automatic initialization procedure in parameter estimation problems with parameter-affine dynamic models. Comput. Chem. Eng. 34(6): 953-964 (2010) - [j127]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Optimized fixed-size kernel models for large data sets. Comput. Stat. Data Anal. 54(6): 1484-1504 (2010) - [j126]Toni Barjas Blanco, Mark Cannon, Bart De Moor:
On efficient computation of low-complexity controlled invariant sets for uncertain linear systems. Int. J. Control 83(7): 1339-1346 (2010) - [j125]Xinhai Liu, Shi Yu, Frizo A. L. Janssens, Wolfgang Glänzel, Yves Moreau, Bart De Moor:
Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal database. J. Assoc. Inf. Sci. Technol. 61(6): 1105-1119 (2010) - [c130]Maarten Breckpot, Toni Barjas Blanco, Bart De Moor:
Flood control of rivers with Model Predictive Control. ACC 2010: 2983-2988 - [c129]Kim Batselier, Bart De Moor:
Maximum likelihood and polynomial system solving. BIBM Workshops 2010: 819-820 - [c128]Oscar Mauricio Agudelo, Jairo Jose Espinosa, Bart De Moor:
Reduction of the computational burden of POD models with polynomial nonlinearities. CDC 2010: 3457-3462 - [c127]Maarten Breckpot, Toni Barjas Blanco, Bart De Moor:
Flood control of rivers with nonlinear model predictive control and moving horizon estimation. CDC 2010: 6107-6112 - [c126]Tillmann Falck, Johan A. K. Suykens, Bart De Moor:
Linear parametric noise models for Least Squares Support Vector Machines. CDC 2010: 6389-6394 - [c125]Tillmann Falck, Johan A. K. Suykens, Johan Schoukens, Bart De Moor:
Nuclear norm regularization for overparametrized Hammerstein systems. CDC 2010: 7202-7207 - [c124]Fabian Ojeda, Tillmann Falck, Bart De Moor, Johan A. K. Suykens:
Polynomial componentwise LS-SVM: Fast variable selection using low rank updates. IJCNN 2010: 1-7 - [c123]Xinhai Liu, Lieven De Lathauwer, Frizo A. L. Janssens, Bart De Moor:
Hybrid Clustering of Multiple Information Sources via HOSVD. ISNN (2) 2010: 337-345 - [c122]Fabian Ojeda, Marco Signoretto, Raf Van de Plas, Etienne Waelkens, Bart De Moor, Johan A. K. Suykens:
Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging. PRIB 2010: 325-334
2000 – 2009
- 2009
- [j124]Hong Sun, Karen Lemmens, Tim Van den Bulcke, Kristof Engelen, Bart De Moor, Kathleen Marchal:
ViTraM: visualization of transcriptional modules. Bioinform. 25(18): 2450-2451 (2009) - [j123]Joke Allemeersch, Steven Van Vooren, Femke Hannes, Bart De Moor, Joris Robert Vermeesch, Yves Moreau:
An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH. BMC Bioinform. 10: 380 (2009) - [j122]Hong Sun, Tijl De Bie, Valerie Storms, Qiang Fu, Thomas Dhollander, Karen Lemmens, Annemieke Verstuyf, Bart De Moor, Kathleen Marchal:
ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules. BMC Bioinform. 10(S-1) (2009) - [j121]Frizo A. L. Janssens, Lin Zhang, Bart De Moor, Wolfgang Glänzel:
Hybrid clustering for validation and improvement of subject-classification schemes. Inf. Process. Manag. 45(6): 683-702 (2009) - [j120]Oscar Mauricio Agudelo, Michel Baes, Jairo Jose Espinosa, Moritz Diehl, Bart De Moor:
Positive Polynomial Constraints for POD-based Model Predictive Controllers. IEEE Trans. Autom. Control. 54(5): 988-999 (2009) - [j119]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Least conservative support and tolerance tubes. IEEE Trans. Inf. Theory 55(8): 3799-3806 (2009) - [c121]Niels Haverbeke, Moritz Diehl, Bart De Moor:
A structure exploiting interior-point method for moving horizon estimation. CDC 2009: 1273-1278 - [c120]Julian Bonilla Alarcon, Moritz Diehl, Filip Logist, Bart De Moor, Jan F. M. Van Impe:
A convex approximation for parameter estimation involving parameter-affine dynamic models. CDC 2009: 4670-4675 - [c119]Tillmann Falck, Johan A. K. Suykens, Bart De Moor:
Robustness analysis for Least Squares kernel based regression: an optimization approach. CDC 2009: 6774-6779 - [c118]Oscar Mauricio Agudelo, Jairo José Espinosa, Bart De Moor:
Acceleration of nonlinear POD models: A neural network approach. ECC 2009: 1547-1552 - [c117]Filip Logist, Bart Huyck, Maarten Fabré, Maarten Verwerft, Bert Pluymers, Jos De Brabanter, Bart De Moor, Jan F. M. Van Impe:
Identification and control of a pilot scale binary distillation column. ECC 2009: 4659-4664 - [c116]Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor:
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. ICANN (1) 2009: 100-110 - [c115]Carlos Alzate, Marcelo Espinoza, Bart De Moor, Johan A. K. Suykens:
Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering. ICANN (2) 2009: 315-324 - [c114]Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janssens, Bart De Moor, Wolfgang Glänzel:
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis. ICDM Workshops 2009: 521-526 - [c113]Hong Sun, Tim Van den Bulcke, Bart De Moor, Karen Lemmens, Kristof Engelen, Kathleen Marchal:
Layout and Post-Processing of Transcriptional Modules. IJCBS 2009: 116-121 - [c112]Anneleen Daemen, Olivier Gevaert, Karin Leunen, Eric Legius, Ignace Vergote, Bart De Moor:
Supervised Classification of Array CGH Data with HMM-Based Feature Selection. Pacific Symposium on Biocomputing 2009: 468-479 - [c111]Xinhai Liu, Shi Yu, Yves Moreau, Bart De Moor, Wolfgang Glänzel, Frizo A. L. Janssens:
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets. SDM 2009: 49-60 - [p2]Ben Van Calster, Olivier Gevaert, Caroline Van Holsbeke, Bart De Moor, Sabine Van Huffel, Dirk Timmerman:
Clinical decision support for ovarian tumor diagnosis using Bayesian models: Results from the IOTA study. Computational Intelligence and Bioengineering 2009: 111-128 - 2008
- [j118]Koenraad Van Leemput, Tim Van den Bulcke, Thomas Dhollander, Bart De Moor, Kathleen Marchal, Piet van Remortel:
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data. Artif. Life 14(1): 49-63 (2008) - [j117]Joris Vertommen, Frizo A. L. Janssens, Bart De Moor, Joost R. Duflou:
Multiple-vector user profiles in support of knowledge sharing. Inf. Sci. 178(17): 3333-3346 (2008) - [j116]Victor Rodriguez, Frizo A. L. Janssens, Koenraad Debackere, Bart De Moor:
On material transfer agreements and visibility of researchers in biotechnology. J. Informetrics 2(1): 89-100 (2008) - [j115]Léon-Charles Tranchevent, Roland Barriot, Shi Yu, Steven Van Vooren, Peter Van Loo, Bert Coessens, Bart De Moor, Stein Aerts, Yves Moreau:
ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res. 36(Web-Server-Issue): 377-384 (2008) - [j114]Fabian Ojeda, Johan A. K. Suykens, Bart De Moor:
Low rank updated LS-SVM classifiers for fast variable selection. Neural Networks 21(2-3): 437-449 (2008) - [j113]Frizo A. L. Janssens, Wolfgang Glänzel, Bart De Moor:
A hybrid mapping of information science. Scientometrics 75(3): 607-631 (2008) - [j112]Bart Vanluyten, Jan C. Willems, Bart De Moor:
Equivalence of state representations for hidden Markov models. Syst. Control. Lett. 57(5): 410-419 (2008) - [c110]Oscar Mauricio Agudelo, Jairo Jose Espinosa, Bart De Moor:
Algorithm for reducing the number of constraints of POD-based predictive controllers. CDC 2008: 4743-4748 - [c109]Julian Bonilla Alarcon, Moritz Diehl, Bart De Moor, Jan F. M. Van Impe:
A nonlinear least squares estimation procedure without initial parameter guesses. CDC 2008: 5519-5524 - [c108]Shi Yu, Steven Van Vooren, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Comparison of vocabularies, representations and ranking algorithms for gene prioritization by text mining. ECCB 2008: 119-125 - [c107]Anneleen Daemen, Olivier Gevaert, Karin Leunen, Vanessa Vanspauwen, Geneviève Michils, Eric Legius, Ignace Vergote, Bart De Moor:
Classification of Sporadic and BRCA1 Ovarian Cancer Based on a Genome-Wide Study of Copy Number Variations. KES (2) 2008: 165-172 - [c106]Anneleen Daemen, Olivier Gevaert, Tijl De Bie, Annelies Debucquoy, Jean-Pascal Machiels, Bart De Moor, Karin Haustermans:
Integrating Microarray and Proteomics Data to Predict the Response of Cetuximab in Patients with Rectal Cancer. Pacific Symposium on Biocomputing 2008: 166-177 - [c105]O. Gaevert, Steven Van Vooren, Bart De Moor:
Integration of Microarray and Textual Data Improves the Prognosis Prediction of Breast, Lung, and Ovarian Cancer Patients. Pacific Symposium on Biocomputing 2008: 279-290 - [c104]Raf Van de Plas, Bart De Moor, Etienne Waelkens:
Discrete wavelet transform-based multivariate exploration of tissue via imaging mass spectrometry. SAC 2008: 1307-1308 - 2007
- [j111]Steven Gillijns, Bart De Moor:
Unbiased minimum-variance input and state estimation for linear discrete-time systems. Autom. 43(1): 111-116 (2007) - [j110]Steven Gillijns, Bart De Moor:
Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough. Autom. 43(5): 934-937 (2007) - [j109]Hui Zhao, Kristof Engelen, Bart De Moor, Kathleen Marchal:
CALIB: a Bioconductor package for estimating absolute expression levels from two-color microarray data. Bioinform. 23(13): 1700-1701 (2007) - [j108]Thomas Dhollander, Qizheng Sheng, Karen Lemmens, Bart De Moor, Kathleen Marchal, Yves Moreau:
Query-driven module discovery in microarray data. Bioinform. 23(19): 2573-2580 (2007) - [j107]Jaganath Chandrasekar, Dennis S. Bernstein, Oscar Barrero, B. L. R. De Moor:
Kalman filtering with constrained output injection. Int. J. Control 80(12): 1863-1879 (2007) - [j106]Luc Hoegaerts, Lieven De Lathauwer, Ivan Goethals, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Efficiently updating and tracking the dominant kernel principal components. Neural Networks 20(2): 220-229 (2007) - [j105]Victor Rodriguez, Frizo A. L. Janssens, Koenraad Debackere, Bart De Moor:
Do material transfer agreements affect the choice of research agendas? The case of biotechnology in Belgium. Scientometrics 71(2): 239-269 (2007) - [j104]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
A Convex Approach to Validation-Based Learning of the Regularization Constant. IEEE Trans. Neural Networks 18(3): 917-920 (2007) - [c103]Jeroen Boets, Katrien De Cock, Bart De Moor:
A mutual information based distance for multivariate Gaussian processes. CDC 2007: 3048-3053 - [c102]Oscar Mauricio Agudelo, Jairo Jose Espinosa, Bart De Moor:
POD-based predictive controller with temperature constraints for a tubular reactor. CDC 2007: 3537-3542 - [c101]Bart Vanluyten, Jan C. Willems, Bart De Moor:
A new approach for the identification of hidden Markov models. CDC 2007: 4901-4905 - [c100]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Convex optimization for the design of learning machines. ESANN 2007: 193-204 - [c99]Joos Vandewalle, Johan A. K. Suykens, Bart De Moor, Amaury Lendasse:
State-of-the-Art and Evolution in Public Data Sets and Competitions for System Identification, Time Series Prediction and Pattern Recognition. ICASSP (4) 2007: 1269-1272 - [c98]Fabian Ojeda, Johan A. K. Suykens, Bart De Moor:
Variable selection by rank-one updates for least squares support vector machines. IJCNN 2007: 2283-2288 - [c97]Frizo A. L. Janssens, Wolfgang Glänzel, Bart De Moor:
Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis. KDD 2007: 360-369 - [c96]Frizo Jansens, Wolfgang Glänzel, Bart De Moor:
Integrating Text Mining and Link Analysis. NATO ASI Mining Massive Data Sets for Security 2007: 243-244 - [c95]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
A Risk Minimization Principle for a Class of Parzen Estimators. NIPS 2007: 1137-1144 - [c94]Raf Van de Plas, Fabian Ojeda, Maarten Dewil, Ludo Van Den Bosch, Bart De Moor, Etienne Waelkens:
Prospective Exploration of Biochemical Tissue Composition via Imaging Mass Spectrometry Guided by Principal Component Analysis. Pacific Symposium on Biocomputing 2007: 458-469 - [c93]Kristiaan Pelckmans, John Shawe-Taylor, Johan A. K. Suykens, Bart De Moor:
Margin based Transductive Graph Cuts using Linear Programming. AISTATS 2007: 363-370 - [i5]Diederik Aerts, Marek Czachor, Bart De Moor:
Geometric Analogue of Holographic Reduced Representation. CoRR abs/0710.2611 (2007) - [i4]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Support and Quantile Tubes. CoRR abs/cs/0703055 (2007) - 2006
- [j103]Kristof Engelen, Bart Naudts, Bart De Moor, Kathleen Marchal:
A calibration method for estimating absolute expression levels from microarray data. Bioinform. 22(10): 1251-1258 (2006) - [j102]Tim Van den Bulcke, Koen Van Leemput, Bart Naudts, Piet van Remortel, Hongwu Ma, Alain Verschoren, Bart De Moor, Kathleen Marchal:
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms. BMC Bioinform. 7: 43 (2006) - [j101]Pieter Monsieurs, Gert Thijs, Abeer A. Fadda, Sigrid C. J. De Keersmaecker, Jozef Vanderleyden, Bart De Moor, Kathleen Marchal:
More robust detection of motifs in coexpressed genes by using phylogenetic information. BMC Bioinform. 7: 160 (2006) - [j100]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Fixed-size Least Squares Support Vector Machines: A Large Scale Application in Electrical Load Forecasting. Comput. Manag. Sci. 3(2): 113-129 (2006) - [j99]Frizo A. L. Janssens, Jacqueline Leta, Wolfgang Glänzel, Bart De Moor:
Towards mapping library and information science. Inf. Process. Manag. 42(6): 1614-1642 (2006) - [j98]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods. Mach. Learn. 62(3): 217-252 (2006) - [j97]Zhaoyang Wan, Bert Pluymers, Mayuresh V. Kothare, Bart De Moor:
Comments on: "Efficient robust constrained model predictive control with a time varying terminal constraint set" by Wan and Kothare. Syst. Control. Lett. 55(7): 618-621 (2006) - [c92]Il Seop Choi, J. Anthony Rossiter, Bert Pluymers, Peter J. Fleming, Bart De Moor:
A robust MPC design for hot rolling mills: a polyhedral invariant sets approach. ACC 2006 - [c91]Steven Gillijns, Oscar Barrero, Jaganath Chandrasekar, B. L. R. De Moor, Dennis S. Bernstein, Aaron J. Ridley:
What is the ensemble Kalman filter and how well does it work? ACC 2006: 1-6 - [c90]Harish J. Palanthandalam-Madapusi, Steven Gillijns, Bart De Moor, Dennis S. Bernstein:
Subsystem identification for nonlinear model updating. ACC 2006: 1-6 - [c89]Bert Pluymers, Mayuresh V. Kothare, Johan A. K. Suykens, Bart De Moor:
Robust synthesis of constrained linear state feedback using LMIs and polyhedral invariant sets. ACC 2006 - [c88]Ivan Markovsky, Jan C. Willems, Bart De Moor:
The Module Structure of ARMAX Systems. CDC 2006: 811-816 - [c87]Steven Gillijns, Bart De Moor:
Data-based Subsystem Identification for Dynamic Model Updating. CDC 2006: 3303-3308 - [c86]Bart Vanluyten, Jan C. Willems, Bart De Moor:
Matrix Factorization and Stochastic State Representations. CDC 2006: 4188-4193 - [c85]Tom Van Herpe, Bert Pluymers, Marcelo Espinoza, Greet Van den Berghe, Bart De Moor:
A minimal model for glycemia control in critically ill patients. EMBC 2006: 5432-5435 - [c84]Kristof Op De Beeck, Irene Y. H. Gu, Liyuan Li, Mats Viberg, Bart De Moor:
Region-Based Statistical Background Modeling for Foreground Object Segmentation. ICIP 2006: 3317-3320 - [c83]Olivier Gevaert, Frank De Smet, Dirk Timmerman, Yves Moreau, Bart De Moor:
Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. ISMB (Supplement of Bioinformatics) 2006: 184-190 - [c82]Shi Yu, Steven Van Vooren, Bert Coessens, Bart De Moor:
Interpreting Gene Profiles from Biomedical Literature Mining with Self Organizing Maps. ISNN (2) 2006: 635-641 - [c81]Tom Bellemans, Bart De Schutter, Geert Wets, Bart De Moor:
Model Predictive Control for Ramp Metering Combined with Extended Kalman Filter-Based Traffic State Estimation. ITSC 2006: 406-411 - [c80]Maja Hadzic, Bart De Moor, Yves Moreau, Arek Kasprzyk:
KSinBIT 2006 PC Co-chairs' Message. OTM Workshops (1) 2006: 647 - [c79]Bert Coessens, Stijn Christiaens, Ruben Verlinden, Yves Moreau, Robert Meersman, Bart De Moor:
Ontology Guided Data Integration for Computational Prioritization of Disease Genes. OTM Workshops (1) 2006: 689-698 - [c78]Bart Vanluyten, Jan C. Willems, Bart De Moor:
Recursive Filtering Using Quasi-Realizations. POSTA 2006: 367-374 - [i3]Diederik Aerts, Marek Czachor, Bart De Moor:
On Geometric Algebra representation of Binary Spatter Codes. CoRR abs/cs/0610075 (2006) - 2005
- [j96]Ivan Markovsky, Bart De Moor:
Linear dynamic filtering with noisy input and output. Autom. 41(1): 167-171 (2005) - [j95]Ivan Markovsky, Jan C. Willems, Paolo Rapisarda, Bart De Moor:
Algorithms for deterministic balanced subspace identification. Autom. 41(5): 755-766 (2005) - [j94]Bert Pluymers, L. Roobrouck, J. Buijs, Johan A. K. Suykens, Bart De Moor:
Constrained linear MPC with time-varying terminal cost using convex combinations. Autom. 41(5): 831-837 (2005) - [j93]Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Identification of MIMO Hammerstein models using least squares support vector machines. Autom. 41(7): 1263-1272 (2005) - [j92]Nathalie Pochet, Frizo A. L. Janssens, Frank De Smet, Kathleen Marchal, Johan A. K. Suykens, Bart De Moor:
M@CBETH: a microarray classification benchmarking tool. Bioinform. 21(14): 3185-3186 (2005) - [j91]Steffen Durinck, Yves Moreau, Arek Kasprzyk, Sean R. Davis, Bart De Moor, Alvis Brazma, Wolfgang Huber:
BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinform. 21(16): 3439-3440 (2005) - [j90]Björn Menten, Filip Pattyn, Katleen De Preter, Piet Robbrecht, Evi Michels, Karen Buysse, Geert Mortier, Anne De Paepe, Steven Van Vooren, Joris Robert Vermeesch, Yves Moreau, Bart De Moor, Stefan Vermeulen, Frank Speleman, Jo Vandesompele:
arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays. BMC Bioinform. 6: 124 (2005) - [j89]Jeroen Boets, Katrien De Cock, Marcelo Espinoza, Bart De Moor:
Clustering time series, subspace identification and cepstral distances. Commun. Inf. Syst. 5(1): 69-96 (2005) - [j88]Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Subset based least squares subspace regression in RKHS. Neurocomputing 63: 293-323 (2005) - [j87]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Building sparse representations and structure determination on LS-SVM substrates. Neurocomputing 64: 137-159 (2005) - [j86]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
The differogram: Non-parametric noise variance estimation and its use for model selection. Neurocomputing 69(1-3): 100-122 (2005) - [j85]Patrick Glenisson, Wolfgang Glänzel, Frizo A. L. Janssens, Bart De Moor:
Combining full text and bibliometric information in mapping scientific disciplines. Inf. Process. Manag. 41(6): 1548-1572 (2005) - [j84]Stein Aerts, Peter Van Loo, Gert Thijs, Herbert Mayer, Rainer de Martin, Yves Moreau, Bart De Moor:
TOUCAN 2: the all-inclusive open source workbench for regulatory sequence analysis. Nucleic Acids Res. 33(Web-Server-Issue): 393-396 (2005) - [j83]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Handling missing values in support vector machine classifiers. Neural Networks 18(5-6): 684-692 (2005) - [j82]Kristiaan Pelckmans, Marcelo Espinoza, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Primal-Dual Monotone Kernel Regression. Neural Process. Lett. 22(2): 171-182 (2005) - [j81]Jan C. Willems, Paolo Rapisarda, Ivan Markovsky, Bart De Moor:
A note on persistency of excitation. Syst. Control. Lett. 54(4): 325-329 (2005) - [j80]Bert Pluymers, Johan A. K. Suykens, Bart De Moor:
Min-max feedback MPC using a time-varying terminal constraint set and comments on "Efficient robust constrained model predictive control with a time-varying terminal constraint set". Syst. Control. Lett. 54(12): 1143-1148 (2005) - [j79]Ivan Markovsky, Jan C. Willems, Sabine Van Huffel, Bart De Moor, Rik Pintelon:
Application of structured total least squares for system identification and model reduction. IEEE Trans. Autom. Control. 50(10): 1490-1500 (2005) - [j78]Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Subspace identification of Hammerstein systems using least squares support vector machines. IEEE Trans. Autom. Control. 50(10): 1509-1519 (2005) - [j77]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Kernel based partially linear models and nonlinear identification. IEEE Trans. Autom. Control. 50(10): 1602-1606 (2005) - [j76]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
A prewhitening-induced bound on the identification error in independent component analysis. IEEE Trans. Circuits Syst. I Regul. Pap. 52-I(3): 546-554 (2005) - [c77]Bert Pluymers, John Anthony Rossiter, Johan A. K. Suykens, Bart De Moor:
The efficient computation of polyhedral invariant sets for linear systems with polytopic uncertainty. ACC 2005: 804-809vol.2 - [c76]Bert Pluymers, John Anthony Rossiter, Johan A. K. Suykens, Bart De Moor:
Interpolation based MPC for LPV systems using polyhedral invariant sets. ACC 2005: 810-815vol.2 - [c75]Oscar Barrero, Dennis S. Bernstein, Bart De Moor:
Spatially localized Kalman filtering for data assimilation. ACC 2005: 3468-3473 - [c74]J. Anthony Rossiter, Yihang Ding, Bert Pluymers, Johan A. K. Suykens, Bart De Moor:
Interpolation based robust MPC with exact constraint handling. CDC/ECC 2005: 302-307 - [c73]Bart Vanluyten, Jan C. Willems, Bart De Moor:
Model Reduction of Systems with Symmetries. CDC/ECC 2005: 826-831 - [c72]Ivan Markovsky, Jan C. Willems, Bart De Moor:
State Representations From Finite Time Series. CDC/ECC 2005: 832-835 - [c71]Kristiaan Pelckmans, Johan A. K. Suykens, Ivan Goethals, Bart De Moor:
On Model Complexity Control in Identification of Hammerstein Systems. CDC/ECC 2005: 1203-1208 - [c70]Ivan Markovsky, Jan C. Willems, Sabine Van Huffel, Bart De Moor:
Software for Approximate Linear System Identification. CDC/ECC 2005: 1559-1564 - [c69]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Imposing Symmetry in Least Squares Support Vector Machines Regression. CDC/ECC 2005: 5716-5721 - [c68]Ivan Goethals, Kristiaan Pelckmans, Luc Hoegaerts, Johan A. K. Suykens, Bart De Moor:
Subspace intersection identification of Hammerstein-Wiener systems. CDC/ECC 2005: 7108-7113 - [c67]Nathalie Pochet, Frizo A. L. Janssens, Frank De Smet, Kathleen Marchal, Ignace Vergote, Johan A. K. Suykens, Bart De Moor:
M@CBETH: Optimizing Clinical Microarray Classification. CSB Workshops 2005: 89-90 - [c66]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Componentwise Support Vector Machines for Structure Detection. ICANN (2) 2005: 643-648 - [c65]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines. IWANN 2005: 1018-1026 - [c64]Tijl De Bie, Patrick Monsieurs, Kristof Engelen, Bart De Moor, Nello Cristianini, Kathleen Marchal:
Discovering Transcriptional Modules from Motif, Chip-Chip and Microarray Data. Pacific Symposium on Biocomputing 2005 - [p1]Qizheng Sheng, Yves Moreau, Frank De Smet, Kathleen Marchal, Bart De Moor:
Advances in Cluster Analysis of Microarray Data. Data Analysis and Visualization in Genomics and Proteomics 2005: 153-173 - [i2]Kristiaan Pelckmans, Ivan Goethals, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Componentwise Least Squares Support Vector Machines. CoRR abs/cs/0504086 (2005) - 2004
- [j75]Peter Antal, Geert Fannes, Dirk Timmerman, Yves Moreau, Bart De Moor:
Using literature and data to learn Bayesian networks as clinical models of ovarian tumors. Artif. Intell. Medicine 30(3): 257-281 (2004) - [j74]Stein Aerts, Peter Van Loo, Yves Moreau, Bart De Moor:
A genetic algorithm for the detection of new cis-regulatory modules in sets of coregulated genes. Bioinform. 20(12): 1974-1976 (2004) - [j73]Nathalie Pochet, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
Systematic benchmarking of microarray data classification: assessing the role of non-linearity and dimensionality reduction. Bioinform. 20(17): 3185-3195 (2004) - [j72]Steffen Durinck, Joke Allemeersch, Vincent Carey, Yves Moreau, Bart De Moor:
Importing MAGE-ML format microarray data into BioConductor. Bioinform. 20(18): 3641-3642 (2004) - [j71]Arie Yeredor, Bart De Moor:
On homogeneous least-squares problems and the inconsistency introduced by mis-constraining. Comput. Stat. Data Anal. 47(3): 455-465 (2004) - [j70]Tony Van Gestel, Johan A. K. Suykens, Bart Baesens, Stijn Viaene, Jan Vanthienen, Guido Dedene, Bart De Moor, Joos Vandewalle:
Benchmarking Least Squares Support Vector Machine Classifiers. Mach. Learn. 54(1): 5-32 (2004) - [j69]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
Computation of the Canonical Decomposition by Means of a Simultaneous Generalized Schur Decomposition. SIAM J. Matrix Anal. Appl. 26(2): 295-327 (2004) - [c63]Bert Pluymers, Johan A. K. Suykens, Bart De Moor:
Linear MPC with time-varying terminal cost using sparse convex combinations and bisection search. CDC 2004: 2029-2034 - [c62]Bert Pluymers, Johan A. K. Suykens, Bart De Moor:
Robust finite-horizon MPC using optimal worst-case closed-loop predictions. CDC 2004: 2503-2508 - [c61]Jaganath Chandrasekar, Oscar Barrero, Aaron J. Ridley, Dennis S. Bernstein, Bart De Moor:
State estimation for linearized MHD flow. CDC 2004: 2584-2589 - [c60]Jan C. Willems, Ivan Markovsky, Paolo Rapisarda, Bart De Moor:
A note on persistency of excitation. CDC 2004: 2630-2631 - [c59]Ivan Markovsky, Jan C. Willems, Sabine Van Huffel, Bart De Moor, Rik Pintelon:
Application of structured total least squares for system identification. CDC 2004: 3382-3387 - [c58]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Partially linear models and least squares support vector machines. CDC 2004: 3388-3393 - [c57]Harish J. Palanthandalam-Madapusi, Steven Gillijns, Aaron J. Ridley, Dennis S. Bernstein, Bart De Moor:
Electric potential estimation with line-of-sight measurements using basis function optimization. CDC 2004: 3625-3630 - [c56]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Sparse LS-SVMs using additive regularization with a penalized validation criterion. ESANN 2004: 435-440 - [c55]Oscar Barrero, B. L. R. De Moor:
Nonparametric regularized time delay estimation. ICASSP (2) 2004: 541-544 - [c54]Kristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor:
Morozov, Ivanov and Tikhonov Regularization Based LS-SVMs. ICONIP 2004: 1216-1222 - [c53]Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
A Comparison of Pruning Algorithms for Sparse Least Squares Support Vector Machines. ICONIP 2004: 1247-1253 - [c52]Tijl De Bie, Johan A. K. Suykens, Bart De Moor:
Learning from General Label Constraints. SSPR/SPR 2004: 671-679 - 2003
- [j68]Peter Antal, Geert Fannes, Dirk Timmerman, Yves Moreau, Bart De Moor:
Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection. Artif. Intell. Medicine 29(1-2): 39-60 (2003) - [j67]Kristof Engelen, Bert Coessens, Kathleen Marchal, Bart De Moor:
MARAN: Normalizing Micro-array Data. Bioinform. 19(7): 893-894 (2003) - [j66]Bart De Moor, Kathleen Marchal, Janick Mathys, Yves Moreau:
Bioinformatics: Organisms from Venus, Technology from Jupiter, Algorithms from Mars. Eur. J. Control 9(2-3): 237-278 (2003) - [j65]Emil-Mihal Muresan, Bart De Moor:
Soccer and Data Mining. Int. J. Comput. Sci. Sport 2(1) (2003) - [j64]Bert Coessens, Gert Thijs, Stein Aerts, Kathleen Marchal, Frank De Smet, Kristof Engelen, Patrick Glenisson, Yves Moreau, Janick Mathys, Bart De Moor:
INCLUSive: a web portal and service registry for microarray and regulatory sequence analysis. Nucleic Acids Res. 31(13): 3468-3470 (2003) - [j63]Delin Chu, Lieven De Lathauwer, Bart De Moor:
A QR-type reduction for computing the SVD of a general matrix product/quotient. Numerische Mathematik 95(1): 101-121 (2003) - [j62]Patrick Glenisson, Janick Mathys, Bart De Moor:
Meta-clustering of gene expression data and literature-based information. SIGKDD Explor. 5(2): 101-112 (2003) - [j61]Katrien De Cock, Bernard Hanzon, Bart De Moor:
On a cepstral norm for an ARMA model and the polar plot of the logarithm of its transfer function. Signal Process. 83(2): 439-443 (2003) - [j60]Geert Ysebaert, Katleen Van Acker, Marc Moonen, Bart De Moor:
Constraints in channel shortening equalizer design for DMT-based systems. Signal Process. 83(3): 641-648 (2003) - [j59]Ivan Goethals, Tony Van Gestel, Johan A. K. Suykens, Paul Van Dooren, Bart De Moor:
Identification of positive real models in subspace identification by using regularization. IEEE Trans. Autom. Control. 48(10): 1843-1847 (2003) - [j58]Axel Nackaerts, Bart De Moor, Rudy Lauwereins:
A formant filtered physical model for wind instruments. IEEE Trans. Speech Audio Process. 11(1): 36-44 (2003) - [j57]Johan A. K. Suykens, Tony Van Gestel, Joos Vandewalle, Bart De Moor:
A support vector machine formulation to PCA analysis and its kernel version. IEEE Trans. Neural Networks 14(2): 447-450 (2003) - [c51]Tom Bellemans, Bart De Schutter, Bart De Moor:
Anticipative model predictive control for ramp metering in freeway networks. ACC 2003: 4077-4082 - [c50]Marcelo Espinoza, Johan A. K. Suykens, Bart De Moor:
Least squares support vector machines and primal space estimation. CDC 2003: 3451-3456 - [c49]Tony Van Gestel, Bart Baesens, Johan A. K. Suykens, Marcelo Espinoza, Dirk-Emma Baestaens, Jan Vanthienen, Bart De Moor:
Bankruptcy prediction with least squares support vector machine classifiers. CIFEr 2003: 1-8 - [c48]Stein Aerts, Peter Van Loo, Gert Thijs, Yves Moreau, Bart De Moor:
Computational detection of cis-regulatory modules. ECCB 2003: 5-14 - [c47]Qizheng Sheng, Yves Moreau, Bart De Moor:
Biclustering microarray data by Gibbs sampling. ECCB 2003: 196-205 - [c46]Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Kernel PLS variants for regression. ESANN 2003: 200-208 - [c45]Andrei A. Tiagounov, Jeroen Buijs, Siep Weiland, Bart De Moor:
Long horizon model predictive control for nonlinear industrial processes. ECC 2003: 2041-2046 - [c44]Axel Nackaerts, Bert Schiettecatte, Bart De Moor:
Non-linear guitar body models. ICMC 2003 - [c43]Bert Schiettecatte, Axel Nackaerts, Bart De Moor:
Real-Time Acoustics Simulation using Mesh-Tracing. ICMC 2003 - [c42]B. Vandermeulen, Joost R. Duflou, Bart De Moor:
The Role of User Profiles in Vector-Based Information Retrieval. IKE 2003: 668-669 - [c41]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Variogram based noise variance estimation and its use in kernel based regression. NNSP 2003: 199-208 - [c40]Patrick Glenisson, Peter Antal, Janick Mathys, Yves Moreau, Bart De Moor:
Evaluation of the Vector Space Representation in Text-Based Gene Clustering. Pacific Symposium on Biocomputing 2003: 391-402 - [c39]Patrick Glenisson, Bert Coessens, Steven Van Vooren, Yves Moreau, Bart De Moor:
Text-Based Gene Profiling with Domain-Specific Views. SWDB 2003: 15-31 - 2002
- [b2]Johan A. K. Suykens, Tony Van Gestel, Jos De Brabanter, Bart De Moor, Joos Vandewalle:
Least Squares Support Vector Machines. World Scientific 2002, ISBN 978-981-238-151-4, pp. 1-308 - [j56]Gert Thijs, Yves Moreau, Frank De Smet, Janick Mathys, Magali Lescot, Stephane Rombauts, Pierre Rouzé, Bart De Moor, Kathleen Marchal:
INCLUSive: INtegrated Clustering, Upstream sequence retrieval and motif Sampling. Bioinform. 18(2): 331-332 (2002) - [j55]Frank De Smet, Janick Mathys, Kathleen Marchal, Gert Thijs, Bart De Moor, Yves Moreau:
Adaptive quality-based clustering of gene expression profiles. Bioinform. 18(5): 735-746 (2002) - [j54]Gert Thijs, Kathleen Marchal, Magali Lescot, Stephane Rombauts, Bart De Moor, Pierre Rouzé, Yves Moreau:
A Gibbs Sampling Method to Detect Overrepresented Motifs in the Upstream Regions of Coexpressed Genes. J. Comput. Biol. 9(2): 447-464 (2002) - [j53]Tony Van Gestel, Johan A. K. Suykens, Gert R. G. Lanckriet, Annemie Lambrechts, Bart De Moor, Joos Vandewalle:
Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis. Neural Comput. 14(5): 1115-1147 (2002) - [j52]Philippe Lemmerling, Sabine Van Huffel, Bart De Moor:
The structured total least-squares approach for non-linearly structured matrices. Numer. Linear Algebra Appl. 9(4): 321-332 (2002) - [j51]Tony Van Gestel, Johan A. K. Suykens, Gert R. G. Lanckriet, Annemie Lambrechts, Bart De Moor, Joos Vandewalle:
Multiclass LS SVMs Moderated Outputs and Coding Decoding Schemes. Neural Process. Lett. 15(1): 45-58 (2002) - [j50]Yves Moreau, Frank De Smet, Gert Thijs, Kathleen Marchal, Bart De Moor:
Functional bioinformatics of microarray data: from expression to regulation. Proc. IEEE 90(11): 1722-1743 (2002) - [j49]Katrien De Cock, Bart De Moor:
Subspace angles between ARMA models. Syst. Control. Lett. 46(4): 265-270 (2002) - [j48]Bart De Schutter, Bart De Moor:
The QR Decomposition and the Singular Value Decomposition in the Symmetrized Max-Plus Algebra Revisited. SIAM Rev. 44(3): 417-454 (2002) - [c38]Stein Aerts, Peter Antal, Dirk Timmerman, Bart De Moor, Yves Moreau:
Web-based Data Collection for Uterine Adnexal Tumors: A Case Study. CBMS 2002: 282-287 - [c37]Ivan Markovsky, Jan C. Willems, Bart De Moor:
Continuous-time errors-in-variables filtering. CDC 2002: 2576-2581 - [c36]Lieven De Lathauwer, Bart De Moor:
On the blind separation of non-circular sources. EUSIPCO 2002: 1-4 - [c35]Bart Hamers, Johan A. K. Suykens, Bart De Moor:
Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models. ICANN 2002: 720-726 - [c34]Axel Nackaerts, Bart De Moor, Rudy Lauwereins:
Measurement of guitar string coupling. ICMC 2002 - [i1]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Intelligence and Cooperative Search by Coupled Local Minimizers. CoRR cs.AI/0210030 (2002) - 2001
- [j47]Philippe Lemmerling, Bart De Moor:
Misfit versus latency. Autom. 37(12): 2057-2067 (2001) - [j46]Gert Thijs, Magali Lescot, Kathleen Marchal, Stephane Rombauts, Bart De Moor, Pierre Rouzé, Yves Moreau:
A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling. Bioinform. 17(12): 1113-1122 (2001) - [j45]Tony Van Gestel, Bart De Moor, Brian D. O. Anderson, Peter Van Overschee:
On Frequency Weighted Balanced Truncation: Hankel Singular Values and Error Bounds. Eur. J. Control 7(6): 584-592 (2001) - [j44]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Intelligence and Cooperative Search by Coupled Local Minimizers. Int. J. Bifurc. Chaos 11(8): 2133-2144 (2001) - [j43]Stijn Viaene, Bart Baesens, Tony Van Gestel, Johan A. K. Suykens, Dirk Van den Poel, Jan Vanthienen, Bart De Moor, Guido Dedene:
Knowledge discovery in a direct marketing case using least squares support vector machines. Int. J. Intell. Syst. 16(9): 1023-1036 (2001) - [j42]Michel Duhoux, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Improved Long-Term Temperature Prediction by Chaining of Neural Networks. Int. J. Neural Syst. 11(1): 1-10 (2001) - [j41]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Optimal control by least squares support vector machines. Neural Networks 14(1): 23-35 (2001) - [j40]Philippe Lemmerling, Leentje Vanhamme, Sabine Van Huffel, Bart De Moor:
IQML-like algorithms for solving structured total least squares problems: a unified view. Signal Process. 81(9): 1935-1945 (2001) - [j39]Tony Van Gestel, Johan A. K. Suykens, Paul Van Dooren, Bart De Moor:
Identification of stable models in subspace identification by using regularization. IEEE Trans. Autom. Control. 46(9): 1416-1420 (2001) - [j38]Tony Van Gestel, Johan A. K. Suykens, Dirk-Emma Baestaens, Annemie Lambrechts, Gert R. G. Lanckriet, Bruno Vandaele, Bart De Moor, Joos Vandewalle:
Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Trans. Neural Networks 12(4): 809-821 (2001) - [j37]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
Independent component analysis and (simultaneous) third-order tensor diagonalization. IEEE Trans. Signal Process. 49(10): 2262-2271 (2001) - [c33]Peter Antal, Geert Fannes, Bart De Moor, Joos Vandewalle, Yves Moreau, Dirk Timmerman:
Extended Bayesian Regression Models: A Symbiotic Application of Belief Networks and Multilayer Perceptrons for the Classification of Ovarian Tumors. AIME 2001: 177-187 - [c32]Tom Bellemans, Bart De Schutter, Bart De Moor:
An improved first-order macroscopic flow model for highway traffic simulation. ACC 2001: 2105-2110 - [c31]Peter Antal, Bart De Moor, Tamás Mészáros, Tadeusz P. Dobrowiecki:
Annotated Bayesian Networks: A Tool to Integrate Textual and Probabilistic Medical Knowledge. CBMS 2001: 177-182 - [c30]Tony Van Gestel, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Automatic relevance determination for Least Squares Support Vector Machines classifiers. ESANN 2001: 13-18 - [c29]Tony Van Gestel, Bart De Moor, Brian D. O. Anderson, Peter Van Overschee:
On frequency weighted balanced truncation: A constructive counterexample to Enns' conjecture. ECC 2001: 2493-2498 - [c28]Tom Schouwenaars, Bart De Moor, Eric Feron, Jonathan P. How:
Mixed integer programming for multi-vehicle path planning. ECC 2001: 2603-2608 - [c27]Tony Van Gestel, Johan A. K. Suykens, Jos De Brabanter, Bart De Moor, Joos Vandewalle:
Kernel Canonical Correlation Analysis and Least Squares Support Vector Machines. ICANN 2001: 384-389 - [c26]Axel Nackaerts, Bart De Moor, Rudy Lauwereins:
Parameter estimation for dual-polarization plucked string models. ICMC 2001 - [c25]Tom Schouten, Bart De Moor:
Subband HTLS. ICMC 2001 - [c24]Gert Thijs, Kathleen Marchal, Magali Lescot, Stephane Rombauts, Bart De Moor, Pierre Rouzé, Yves Moreau:
A Gibbs sampling method to detect over-represented motifs in the upstream regions of co-expressed genes. RECOMB 2001: 305-312 - 2000
- [j36]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
A Multilinear Singular Value Decomposition. SIAM J. Matrix Anal. Appl. 21(4): 1253-1278 (2000) - [j35]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
On the Best Rank-1 and Rank-(R1 , R2, ... , RN) Approximation of Higher-Order Tensors. SIAM J. Matrix Anal. Appl. 21(4): 1324-1342 (2000) - [j34]Delin Chu, Lieven De Lathauwer, Bart De Moor:
On the Computation of the Restricted Singular Value Decomposition via the Cosine-Sine Decomposition. SIAM J. Matrix Anal. Appl. 22(2): 580-601 (2000) - [j33]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
Fetal electrocardiogram extraction by blind source subspace separation. IEEE Trans. Biomed. Eng. 47(5): 567-572 (2000) - [j32]Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Robust local stability of multilayer recurrent neural networks. IEEE Trans. Neural Networks Learn. Syst. 11(1): 222-229 (2000) - [c23]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 - [c22]Tony Van Gestel, Johan A. K. Suykens, Paul Van Dooren, Bart De Moor:
Imposing stability in subspace identification by regularization. CDC 2000: 1555-1560 - [c21]Katrien De Cock, Bart De Moor:
Subspace angles between linear stochastic models. CDC 2000: 1561-1566 - [c20]Binning Chen, Athina P. Petropulu, Lieven De Lathauwer, Bart De Moor:
Blind MIMO system identification based on cross-polyspectra. EUSIPCO 2000: 1-4 - [c19]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
An algebraic ICA algorithm for 3 sources and 2 sensors. EUSIPCO 2000: 1-4 - [c18]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
SVD-based methodologies for fetal electrocardiogram extraction. ICASSP 2000: 3771-3774 - [c17]Bart Baesens, Stijn Viaene, Tony Van Gestel, Johan A. K. Suykens, Guido Dedene, Bart De Moor, Jan Vanthienen:
An empirical assessment of kernel type performance for least squares support vector machine classifiers. KES 2000: 313-316 - [c16]Stijn Viaene, Bart Baesens, Tony Van Gestel, Johan A. K. Suykens, Dirk Van den Poel, Jan Vanthienen, Bart De Moor, Guido Dedene:
Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case. PKDD 2000: 657-664 - [c15]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
An algebraic approach to the blind identification of paraunitary filters. WCNC 2000: 1162-1165
1990 – 1999
- 1999
- [j31]Bart De Schutter, Bart De Moor:
On the Sequence of Consecutive Powers of a Matrix in a Boolean Algebra. SIAM J. Matrix Anal. Appl. 21(1): 328-354 (1999) - [j30]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Lur'e systems with multilayer perceptron and recurrent neural networks: absolute stability and dissipativity. IEEE Trans. Autom. Control. 44(4): 770-774 (1999) - [j29]Wouter Favoreel, Bart De Moor, Peter Van Overschee:
Subspace identification of bilinear systems subject to white inputs. IEEE Trans. Autom. Control. 44(6): 1157-1165 (1999) - [c14]Baibing Li, Bart De Moor:
Dynamic total least squares estimation of intersection traffic flow patterns. ECC 1999: 604-608 - [c13]Wouter Favoreel, Sabine Van Huffel, Bart De Moor, Vasile Sima, Michel Verhaegen:
Comparative study between three subspace identification algorithms. ECC 1999: 821-826 - [c12]Erik I. Verriest, Bart De Moor:
Multi-mode system identification. ECC 1999: 2608-2613 - [c11]Peter Van Overschee, Bart De Moor:
Optimal PID control of a chemical batch reactor. ECC 1999: 3262-3267 - [c10]Baibing Li, Bart De Moor:
Information measure based stochastic system identification of ATM network traffic. ICASSP 1999: 2683-2686 - [c9]Baibing Li, Bart De Moor:
Statistical division based modeling for multimedia network traffic. ISSPA 1999: 27-30 - 1998
- [j28]Herman Verrelst, Kristel Van Acker, Johan A. K. Suykens, Bart Motmans, Bart De Moor, Joos Vandewalle:
Application of NLq Neural Control Theory to a Ball and Beam System. Eur. J. Control 4(2): 148-157 (1998) - [j27]Bart De Schutter, Bart De Moor:
Optimal Traffic Light Control for a Single Intersection. Eur. J. Control 4(3): 260-276 (1998) - [j26]Bart De Schutter, Bart De Moor:
The QR Decomposition and the Singular Value Decomposition in the Symmetrized Max-Plus Algebra. SIAM J. Matrix Anal. Appl. 19(2): 378-406 (1998) - [c8]Katrien De Cock, Bart De Moor:
Stochastic system identification for ATM network traffic models: A time domain approach. EUSIPCO 1998: 1-4 - 1997
- [j25]Peter Van Overschee, Bart De Moor, Wouter Dehandschutter, Jan Swevers:
A subspace algorithm for the identification of discrete time frequency domain power spectra. Autom. 33(12): 2147-2157 (1997) - [j24]Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
NLq Theory: A Neural Control Framework with Global Asymptotic Stability Criteria. Neural Networks 10(4): 615-637 (1997) - [j23]Jeroen Dehaene, Yi Cheng, Bart De Moor:
Calculation of the structured singular value with gradient-based optimization algorithms on a Lie group of structured unitary matrices. IEEE Trans. Autom. Control. 42(11): 1596-1600 (1997) - [j22]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
NLq theory: checking and imposing stability of recurrent neural networks for nonlinear modeling. IEEE Trans. Signal Process. 45(11): 2682-2691 (1997) - [c7]Bart De Schutter, Bart De Moor:
The Extended Linear Complementary Problem and the Modeling and Analysis of Hybrid Systems. Hybrid Systems 1997: 70-85 - [c6]Bart De Schutter, Bart De Moor:
Generalized Linear Complementary Problems and the Analysis of Continuously Variable Systems and Discrete Event Systems. HART 1997: 409-414 - [c5]Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Robust NLq neural control theory. ICNN 1997: 2396-2401 - 1996
- [b1]Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Artificial neural networks for modelling and control of non-linear systems. Kluwer 1996, ISBN 978-0-7923-9678-9, pp. I-XII, 1-235 - [j21]Bart De Schutter, Bart De Moor:
A method to find all solutions of a system of multivariate polynomial equalities and inequalities in the max algebra. Discret. Event Dyn. Syst. 6(2): 115-138 (1996) - [j20]Johan A. K. Suykens, Philippe Lemmerling, Wouter Favoreel, Bart De Moor, M. Crepel, P. Briol:
Modelling the Belgian Gas Consumption Using Neural Networks. Neural Process. Lett. 4(3): 157-166 (1996) - [j19]Peter Van Overschee, Bart De Moor:
Continuous-time frequency domain subspace system identification. Signal Process. 52(2): 179-194 (1996) - [j18]Geert Schelfhout, Bart De Moor:
A note on closed-loop balanced truncation. IEEE Trans. Autom. Control. 41(10): 1498-1500 (1996) - [j17]Philippe Lemmerling, Bart De Moor, Sabine Van Huffel:
On the equivalence of constrained total least squares and structured total least squares. IEEE Trans. Signal Process. 44(11): 2908-2911 (1996) - [c4]Lieven De Lathauwer, Bart De Moor, Joos Vandewalle:
Blind source separation by simultaneous third-order tensor diagonalization. EUSIPCO 1996: 1-4 - [c3]Philippe Lemmerling, Sabine Van Huffel, Bart De Moor:
Structured total least squares methods in signal processing. EUSIPCO 1996: 1-4 - 1995
- [j16]Christiaan Moons, Bart De Moor:
Parameter identification of induction motor drives. Autom. 31(8): 1137-1147 (1995) - [j15]Peter Van Overschee, Bart De Moor:
A unifying theorem for three subspace system identification algorithms. Autom. 31(12): 1853-1864 (1995) - [j14]Peter Van Overschee, Bart De Moor:
Choice of state-space basis in combined deterministic-stochastic subspace identification. Autom. 31(12): 1877-1883 (1995) - [j13]Bart De Schutter, Bart De Moor:
The extended linear complementarity problem. Math. Program. 71: 289-325 (1995) - [c2]Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
NLq theory: unifications in the theory of neural networks, systems and control. ESANN 1995 - 1994
- [j12]Peter Van Overschee, Bart De Moor:
N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems. Autom. 30(1): 75-93 (1994) - [j11]Bart De Moor, Michel Gevers, Graham C. Goodwin:
L2-overbiased, L2-underbiased and L2-unbiased estimation of transfer functions. Autom. 30(5): 893-898 (1994) - [j10]Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points. Neural Networks 7(5): 819-831 (1994) - [j9]Bart De Moor:
On the Structure of Generalized Singular Value and QR Decompositions. SIAM J. Matrix Anal. Appl. 15(1): 347-358 (1994) - [j8]Yi Cheng, Bart De Moor:
Robustness analysis and control system design for a hydraulic servo system. IEEE Trans. Control. Syst. Technol. 2(3): 183-197 (1994) - [j7]Bart De Moor:
Total least squares for affinely structured matrices and the noisy realization problem. IEEE Trans. Signal Process. 42(11): 3104-3113 (1994) - 1993
- [j6]Peter Van Overschee, Bart De Moor:
Subspace algorithms for the stochastic identification problem, . Autom. 29(3): 649-660 (1993) - [j5]Bart De Moor:
The singular value decomposition and long and short spaces of noisy matrices. IEEE Trans. Signal Process. 41(9): 2826-2838 (1993) - 1992
- [j4]Bart De Moor, Lieven Vandenberghe, Joos Vandewalle:
The generalized linear complementarity problem and an algorithm to find all its solutions. Math. Program. 57: 415-426 (1992) - [j3]Bart De Moor, Paul Van Dooren:
Generalizations of the Singular Value and QR-Decompositions. SIAM J. Matrix Anal. Appl. 13(4): 993-1014 (1992) - 1991
- [j2]Bart De Moor:
Generalizations of the singular value and QR decompositions. Signal Process. 25(2): 135-146 (1991)
1980 – 1989
- 1988
- [j1]Bart De Moor, Lieven Vandenberghe, Joos Vandewalle:
Computing all invariant states of a neural network. Neural Networks 1(Supplement-1): 89-90 (1988) - [c1]Bart De Moor, Marc Moonen, Lieven Vandenberghe, Joos Vandewalle:
A geometrical approach for the identification of state space models with singular value decomposition. ICASSP 1988: 2244-2247
Coauthor Index
[j159] [c145] [c144] [i6] [c143] [c142] [c141] [j144] [j143] [j142] [j141] [c133] [c132] [b3] [j138] [j137] [j136] [j131] [j130] [j129] [j125] [j123] [c114] [c111] [j115] [c108] [j108] [c83] [c80] [c79] [j91] [j90] [j84] [p1] [j75] [j74] [j72] [j68] [j66] [j64] [c48] [c47] [c40] [c39] [j56] [j55] [j54] [j50] [c38] [j46] [c33] [c24]
[j174] [j172] [i22] [i20] [c156] [c155] [c154] [i18] [i17] [j158] [c147] [j156] [j155] [j153] [c144] [i9] [i8] [i7] [j141] [j140] [c135] [c134] [j137] [j135] [j133] [j132] [j130] [j127] [c126] [c125] [c124] [c122] [j119] [c119] [c116] [c115] [j114] [j106] [j104] [c100] [c99] [c98] [c95] [c93] [i4] [j100] [j98] [c89] [j94] [j93] [j92] [j88] [j87] [j86] [j83] [j82] [j80] [j78] [j77] [c77] [c76] [c74] [c71] [c69] [c68] [c67] [c66] [c65] [i2] [j73] [j70] [c63] [c62] [c58] [c56] [c54] [c53] [c52] [j59] [j57] [c50] [c49] [c46] [c41] [b2] [j53] [j51] [c35] [i1] [j44] [j43] [j42] [j41] [j39] [j38] [c30] [c27] [j32] [c22] [c17] [c16] [j30] [j28] [j24] [j22] [c5] [b1] [j20] [c2] [j10]
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