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Journal Articles


1. Olikier, Guillaume; Absil, Pierre-Antoine. On the Continuity of the Tangent Cone to the Determinantal Variety. In: Set-Valued and Variational Analysis, Vol. 30, p. 769-788 (2022). doi:10.1007/s11228-022-00629-0. http://hdl.handle.net/2078.1/262947

2. Van Hoorebeeck, Loïc; Absil, Pierre-Antoine; Papavasiliou, Anthony. Solving non-convex economic dispatch with valve-point effects and losses with guaranteed accuracy. In: International Journal of Electrical Power & Energy Systems, Vol. 134, p. 107143 (2022). doi:10.1016/j.ijepes.2021.107143. http://hdl.handle.net/2078.1/249814

3. Dirksen, Sjoerd; Genzel, Martin; Stollenwerk, Alexander; Jacques, Laurent. The Separation Capacity of Random Neural Networks. In: Journal of Machine Learning Research, Vol. 23, no.209, p. 1--47 (2022). (Accepté/Sous presse). http://hdl.handle.net/2078.1/267732

4. Dong, Shuyu; Absil, Pierre-Antoine; Gallivan, K.A. Riemannian gradient descent methods for graph-regularized matrix completion. In: Linear Algebra and its Applications, Vol. 623, p. 193-235 (2021). doi:10.1016/j.laa.2020.06.010. http://hdl.handle.net/2078.1/246399

5. Marrinan, Tim; Absil, Pierre-Antoine; Gillis, Nicolas. On a minimum enclosing ball of a collection of linear subspaces. In: Linear Algebra and its Applications, Vol. 625, p. 248-278 (2021). doi:10.1016/j.laa.2021.05.006. http://hdl.handle.net/2078.1/246488

6. Wang, Lei; Gao, Bin; Liu, Xin. Multipliers Correction Methods for Optimization Problems over the Stiefel Manifold. In: CSIAM Transactions on Applied Mathematics, Vol. 2, no.3, p. 508-531 (2021). doi:10.4208/csiam-am.so-2020-0008. http://hdl.handle.net/2078.1/250709

7. Gerniers, Alexander; Bricard, Orian; Dupont, Pierre. MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data. In: Bioinformatics, Vol. 37, no. 19, p. 3220-3227 (2021). doi:10.1093/bioinformatics/btab239. http://hdl.handle.net/2078.1/245010

8. Gao, Bin; Absil, Pierre-Antoine. A Riemannian rank-adaptive method for low-rank matrix completion. In: Computational Optimization and Applications, (2021). doi:10.1007/s10589-021-00328-w. http://hdl.handle.net/2078.1/253601

9. Hamer, Victor; Dupont, Pierre. An Importance Weighted Feature Selection Stability Measure. In: Journal of Machine Learning Research, Vol. 22, no.116, p. 1-57 (2021). http://hdl.handle.net/2078.1/246806

10. Gao, Bin; Nguyen, Thanh Son; Absil, Pierre-Antoine; Stykel, Tatjana. Riemannian Optimization on the Symplectic Stiefel Manifold. In: SIAM Journal on Optimization, Vol. 31, no.2, p. 1546-1575 (2021). doi:10.1137/20m1348522. http://hdl.handle.net/2078.1/249366

11. Nguyen, Thanh Son; Absil, Pierre-Antoine; Gao, Bin; Stykel, Tatjana. Symplectic eigenvalue problem via trace minimization and Riemannian optimization. In: SIAM Journal on Matrix Analysis and Applications, Vol. 42, no.4, p. 1732-1757 (2021). doi:10.1137/21m1390621. http://hdl.handle.net/2078.1/255487

12. Musolas, Antoni; Massart, Estelle; Hendrickx, Julien; Absil, Pierre-Antoine; Marzouk, Youssef. Low-rank multi-parametric covariance identification. In: BIT Numerical Mathematics, Vol. 62, p. 221-249 (2021). doi:10.1007/s10543-021-00867-y. http://hdl.handle.net/2078.1/246400

13. Berger, Guillaume O.; Absil, Pierre-Antoine; De Lathauwer, Lieven; Jungers, Raphaël M.; Van Barel, Marc. Equivalent polyadic decompositions of matrix multiplication tensors. In: Journal of Computational and Applied Mathematics, Vol. 406, p. 113941 (2022). doi:10.1016/j.cam.2021.113941. http://hdl.handle.net/2078.1/255502

14. Coelho, Frederico; Costa, Marcelo; Verleysen, Michel; Braga, Antônio P. LASSO multi-objective learning algorithm for feature selection. In: Soft Computing, Vol. 24, no.4, p. 9 (2020). doi:10.1007/s00500-020-04734-w. http://hdl.handle.net/2078.1/226952

15. Yuan, Xinru; Huang, Wen; Absil, Pierre-Antoine; Gallivan, Kyle A. Computing the matrix geometric mean: Riemannian versus Euclidean conditioning, implementation techniques, and a Riemannian BFGS method. In: Numerical Linear Algebra with Applications, Vol. 27, no.5, p. 2321 (2020). doi:10.1002/nla.2321. http://hdl.handle.net/2078.1/235049

16. Mulders, Dounia; de Bodt, Cyril; Bjelland, Johannes; Pentland, Alex; Verleysen, Michel; de Montjoye, Yves-Alexandre. Inference of node attributes from social network assortativity. In: Neural Computing and Applications, Vol. 32, no. /, p. 18023-18043 (December 2020). doi:10.1007/s00521-018-03967-z. http://hdl.handle.net/2078.1/209834

17. Branders, Vincent; Schaus, Pierre; Dupont, Pierre. Identifying gene-specific subgroups: an alternative to biclustering. In: BMC Bioinformatics, Vol. 20, no.625, p. 13 (2019). doi:10.1186/s12859-019-3289-0. http://hdl.handle.net/2078.1/223506

18. Gousenbourger, Pierre-Yves; Massart, Estelle; Absil, Pierre-Antoine. Data Fitting on Manifolds with Composite Bézier-Like Curves and Blended Cubic Splines. In: Journal of Mathematical Imaging and Vision, Vol. 61, no. 5, p. 645-671 (2018). doi:10.1007/s10851-018-0865-2. http://hdl.handle.net/2078.1/208456

19. Kesiman, Made Windu Antara; Valy, Dona; Burie, Jean-christophe; Paulus, Erick; Sunarya, I. Made Gede; Hadi, Setiawan; Sok, Kim Heng; Ogier, Jean-Marc. Southeast Asian palm leaf manuscript images - a review of handwritten text line segmentation methods and new challenges. In: Journal of Electronic Imaging, Vol. 26, no.1, p. 1-15 (2017). doi:10.1117/1.JEI.26.1.011011. http://hdl.handle.net/2078.1/197291

20. Coelho, Frederico; Castro, Cristiano; Braga, Antônio P.; Verleysen, Michel. Semi-supervised relevance index for feature selection. In: Neural Computing and Applications, Vol. 31, p. 989-997 (2017). doi:10.1007/s00521-017-3062-0. http://hdl.handle.net/2078.1/258302

21. Cambier, Léopold; Absil, Pierre-Antoine. Robust low-rank matrix completion by Riemannian optimization. In: SIAM Journal on Scientific Computing, Vol. 38, no. 5, p. S440-S460 (2016). doi:10.1137/15M1025153. http://hdl.handle.net/2078.1/172843

22. Frénay, Benoît; Verleysen, Michel. Reinforced Extreme Learning Machines for Fast Robust Regression in the Presence of Outliers. In: IEEE Transactions on Cybernetics, no. 99, p. 13 (17/12/2015). doi:10.1109/TCYB.2015.2504404. http://hdl.handle.net/2078.1/171346

23. Boumal, Nicolas; Absil, Pierre-Antoine. Low-rank matrix completion via preconditioned optimization on the Grassmann manifold. In: Linear Algebra and Its Applications, Vol. 475, p. 200-239 (June 2015). doi:10.1016/j.laa.2015.02.027. http://hdl.handle.net/2078.1/157561

24. De Visscher, Ruben; Delouille, Véronique; Dupont, Pierre; Deledalle, Charles-Alban. Supervised classification of solar features using prior information. In: Journal of Space Weather and Space Climate, Vol. 5, no.A34, p. 1-12 (2015). doi:10.1051/swsc/2015033. http://hdl.handle.net/2078.1/166547

25. Paul, Jérôme; D'Ambrosio, Roberto; Dupont, Pierre. Kernel methods for heterogeneous feature selection. In: Neurocomputing, Vol. 169, p. 187-195 (2015). doi:10.1016/j.neucom.2014.12.098. http://hdl.handle.net/2078.1/162795

26. Paul, Jérôme; Dupont, Pierre. Inferring statistically significant features from random forests. In: Neurocomputing, Vol. 150, no.part B, p. 471–480 (20 February 2015). doi:10.1016/j.neucom.2014.07.067. http://hdl.handle.net/2078.1/153478

27. Keim, Daniel A.; Munzner, Tamara; Rossi, Fabrice; Verleysen, Michel. Bridging Information Visualization with Machine Learning. In: Dagstuhl Reports, Vol. 5, no. 3, p. 1-27 (2015). doi:10.4230/DagRep.5.3.1. http://hdl.handle.net/2078.1/171355

28. Frénay, Benoît; Verleysen, Michel. Classification in the Presence of Label Noise: a Survey. In: IEEE Transactions on Neural Networks and Learning Systems, Vol. 25, no. 5, p. 845-869 (10/04/2015). doi:10.1109/TNNLS.2013.2292894. http://hdl.handle.net/2078.1/138145

29. Frénay, Benoît; Doquire, Gauthier; Verleysen, Michel. Estimating Mutual information for feature selection in the presence of label noise. In: Computational Statistics & Data Analysis, Vol. 71, p. 832-848 (1 May 2013). doi:10.1016/j.csda.2013.05.001. http://hdl.handle.net/2078.1/138189

30. Frénay, Benoît; Verleysen, Michel. Pointwise probability reinforcements for robust statistical inference. In: Neural Networks, Vol. 50, p. 124-141 (14 November 2013). doi:10.1016/j.neunet.2013.11.012. http://hdl.handle.net/2078.1/138178

31. Bernard, G.; Verleysen, Michel; Lee, John Aldo. SU-C-18A-03: Automatic Organ at Risk Delineation with Machine Learning Techniques. In: Medical Physics, Vol. 41, no.6, p. 101 (2014). doi:10.1118/1.4887830. http://hdl.handle.net/2078.1/156927

32. Peluffo Ordoñez, Diego Hernan; Lee, John Aldo; Verleysen, Michel. Short review of dimensionality reduction methods based on stochastic neighbour embedding. In: Advances in Self-Organizing Maps and Learning Vector Quantization, Vol. 295, no.part I, p. 65-74 (2014). doi:10.1007/978-3-319-07695-9_6. http://hdl.handle.net/2078.1/156932

33. Ho, Trong Viet; Deville, Yves; Bonaventure, Olivier. Multi-objective traffic engineering for data center networks. In: Computer Networks, Vol. 65, p. 167–182 (2014). doi:10.1016/j.comnet.2014.03.018. http://hdl.handle.net/2078.1/142722

34. Mairy, Jean-Baptiste; van Hentenryck, Pascal; Deville, Yves. Optimal and efficient filtering algorithms for table constraints. In: Constraints : an international journal, Vol. 19, no.1, p. 77-120 (2014). doi:10.1007/s10601-013-9156-0. http://hdl.handle.net/2078.1/140945

35. Frénay, Benoît; Doquire, Gauthier; Verleysen, Michel. Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification. In: Neurocomputing, Vol. 112, p. 64-78 (2013). doi:10.1016/j.neucom.2012.12.051. http://hdl.handle.net/2078.1/138203

36. Eirola, Emile; Doquire, Gauthier; Verleysen, Michel; Landasse, Amaury. Distance estimation in numerical data sets with missing values. In: Information Sciences, Vol. 240, p. 115-128 (10/08/2013). doi:10.1016/j.ins.2013.03.043. http://hdl.handle.net/2078.1/140941

37. Doquire, Gauthier; Verleysen, Michel. Mutual information-based feature selection for multilabel classification. In: Neurocomputing, Vol. 122, p. 148-155 (25/12/2013). doi:10.1016/j.neucom.2013.06.035. http://hdl.handle.net/2078.1/141003

38. Frénay, Benoît; van Heeswijk, Mark; Miche, Yoan; Verleysen, Michel; Lendasse, Amaury. Feature selection for nonlinear models with extreme learning machines. In: Neurocomputing, Vol. 102, p. 111-124 (15 February 2013). doi:10.1016/j.neucom.2011.12.055. http://hdl.handle.net/2078.1/116535

39. Hernandez Lobato, Daniel; Hernandez Lobato, José Miguel; Dupont, Pierre. Generalized spike-and-slab priors for bayesian group feature selection using expectation propagation. In: Journal of Machine Learning Research, Vol. 14, p. 1891-1945 (2013). http://hdl.handle.net/2078.1/133746

40. Frénay, Benoît; Doquire, Gauthier; Verleysen, Michel. Is mutual information adequate for feature selection in regression?. In: Neural Networks, Vol. 48, p. 1-7 (4 July 2013). doi:10.1016/j.neunet.2013.07.003. http://hdl.handle.net/2078.1/138199

41. Doquire, Gauthier; Verleysen, Michel. A graph Laplacian based approach to semi-supervised feature selection for regression problems. In: Neurocomputing, Vol. 121, p. 5-13 (09/12/2013). doi:10.1016/j.neucom.2012.10.028. http://hdl.handle.net/2078.1/140999

42. Lee, John Aldo; Renard, Emilie; Bernard, G.; Dupont, Pierre; Verleysen, M. Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. In: Neurocomputing, Vol. 112, no. 1, p. 92-108 (2013). doi:10.1016/j.neucom.2012.12.036. http://hdl.handle.net/2078.1/135365

43. Schaus, Pierre; Régin, Jean-Charles. Bound-consistent spread constraint. In: EURO Journal on Computational Optimization, (2013). (Accepté/Sous presse). http://hdl.handle.net/2078.1/141320

44. de Montjoye, Yves-Alexandre; Hidalgo, César A.; Verleysen, Michel; Blondel, Vincent. Unique in the Crowd: The privacy bounds of human mobility. In: Scientific Reports, Vol. 3, no.1376, p. 1-5 (March 2013). doi:10.1038/srep01376. http://hdl.handle.net/2078.1/127341

45. Deville, Yves; Van Hentenryck, Pascal; Mairy, Jean-Baptiste. Domain consistency with forbidden values. In: Constraints : an international journal, Vol. 18, no.3, p. 377-403 (2013). doi:10.1007/s10601-012-9135-x. http://hdl.handle.net/2078.1/141299

46. Walkinshaw, Neil; Lambeau, Bernard; Damas, Christophe; Bogdanov, Kirill; Dupont, Pierre. STAMINA: A Competition to Encourage the Development and Assessment of Software Model Inference Techniques. In: Empirical Software Engineering : an international journal, Vol. 18, no.4, p. 791-824 (2013). doi:10.1007/s10664-012-9210-3. http://hdl.handle.net/2078.1/141236

47. Doquire, Gauthier; Verleysen, Michel. Feature selection with missing data using mutual information estimators. In: Neurocomputing, Vol. 90, no.1, p. 3-11 (August 2012). doi:10.1016/j.neucom.2012.02.031. http://hdl.handle.net/2078.1/116536

48. Fino, L.N.S.; Renaux, Christian; Flandre, Denis; Gimenez, P. Experimental Study of the OCTO SOI nMOSFET and Its Application in Analog Integrated Circuits. In: ECS Transactions, Vol. 49, no.1, p. 527-534 (2012). doi:10.1149/04901.0527ecst. http://hdl.handle.net/2078.1/128604

49. de Lannoy, Gaël; François, Damien; Delbeke, Jean; Verleysen, Michel. Weighted conditional random fields for supervised interpatient heartbeat classification. In: IEEE Transactions on Biomedical Engineering, Vol. 59, no. 1, p. 241-7 (2012). doi:10.1109/TBME.2011.2171037. http://hdl.handle.net/2078.1/111096

50. Mouthuy, Sébastien; Van Hentenryck, Pascal; Deville, Yves. Constraint-Based Very Large-Scale Neighborhood Search. In: Constraints : an international journal, Vol. 17, no. 2, p. 87-122 (2012). http://hdl.handle.net/2078.1/124299

51. Frénay, Benoît; Verleysen, Michel. Parameter-insensitive kernel in extreme learning for non-linear support vector regression. In: Neurocomputing, Vol. 74, no.16, p. 2526-2531 (September 2011). doi:10.1016/j.neucom.2010.11.037. http://hdl.handle.net/2078.1/116543

52. De Decker, Arnaud; François, Damien; Verleysen, Michel; Lee, John Aldo. Mode estimation in high-dimensional spaces with flat-top kernels: Application to image denoising. In: Neurocomputing, Vol. 74, no. 9, p. 1402-1410 (April 2011). doi:10.1016/j.neucom.2010.12.013. http://hdl.handle.net/2078.1/82249

53. Piater, Justus; Jodogne, Sébastien; Detry, Renaud; Kraft, Dirk; Krüger, Norbert; Kroemer, Oliver; Peters, Jan. Learning visual representations for perception-action systems. In: The International Journal of Robotics Research, Vol. 30, no.3, p. 294-307 (2010). doi:10.1177/0278364910382464. http://hdl.handle.net/2078.1/257393

54. Doquire, Gauthier; de Lannoy, Gaël; François, Damien; Verleysen, Michel. Feature selection for supervised inter-patient heart beat classification. In: Computational Intelligence and Neuroscience, Vol. 2011, no. 643816, p. 1-9 (2011). doi:10.1155/2011/643816. http://hdl.handle.net/2078.1/82235

55. Thomas, Isabelle; Frankhauser, Pierre; Frénay, Benoît; Verleysen, Michel. Clustering patterns of urban built-up areas with curves of fractal scaling behaviour. In: Environment and Planning B. Planning and Design, Vol. 37, no. 5, p. 942-954 (2010). doi:10.1068/b36039. http://hdl.handle.net/2078.1/33417

56. De Decker, Arnaud; Lee, John Aldo; Verleysen, Michel. A principled approach to image denoising with similarity kernels involving patches. In: Neurocomputing, Vol. 73, no. 7-9, p. 1199-1209 (2010). doi:10.1016/j.neucom.2009.12.022. http://hdl.handle.net/2078.1/33961

57. Lee, John Aldo; Verleysen, Michel. Scale-independent quality criteria for dimensionality reduction. In: Pattern Recognition Letters, Vol. 31, no. 14, p. 2248-2257 (2010). doi:10.1016/j.patrec.2010.04.013. http://hdl.handle.net/2078.1/34378

58. Journée, Michel; Bach, F.; Absil, Pierre-Antoine; Sepulchre, Rodolphe. Low-rank Optimization On the Cone of Positive Semidefinite Matrices. In: SIAM Journal on Optimization, Vol. 20, no. 5, p. 2327-2351 (2010). doi:10.1137/080731359. http://hdl.handle.net/2078.1/33576

59. Zampelli, Stephane; Deville, Yves; Solnon, Christine. Solving subgraph isomorphism problems with constraint programming. In: Constraints : an international journal, Vol. 15, no. 3, p. 327-353 (2010). doi:10.1007/s10601-009-9074-3. http://hdl.handle.net/2078.1/33811


Conference Papers


1. Jodogne, Sébastien. Client-Side Application of Deep Learning Models Through Teleradiology. In: Studies in Health Technology and Informatics. Vol. 302, no.1, p. 997-1001 (2023). Maria Hägglund et al. 2023 xxx. doi:10.3233/shti230325. http://hdl.handle.net/2078.1/275150

2. Gerniers, Alexander; Dupont, Pierre. MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. In: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022, 978-1-6654-6819-0, p. 148-153 xxx. doi:10.1109/bibm55620.2022.9995176. http://hdl.handle.net/2078.1/271036

3. Jodogne, Sébastien. Importing and serving open-data medical images to support Artificial Intelligence research. In: Insights into Imaging. Vol. 13, no. S1, p. 6. SpringerOpen, 2021 xxx. doi:10.1186/s13244-022-01168-w. http://hdl.handle.net/2078.1/257256

4. Hamer, Victor; Dupont, Pierre. Robust Selection Stability Estimation in Correlated Spaces. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Vol. 1, no.1, p. 446-461 (2021). Springer, 2021 xxx. http://hdl.handle.net/2078.1/251845

5. Gao, Bin; Nguyen, Thanh Son; Absil, Pierre-Antoine; Stykel, Tatjana. Geometry of the Symplectic Stiefel Manifold Endowed with the Euclidean Metric. In: Lecture Notes in Computer Science : Geometric Science of Information, Springer International Publishing,2021, 2021, 978-3-030-80208-0, p. 789-796 xxx. doi:10.1007/978-3-030-80209-7_85. http://hdl.handle.net/2078.1/249751

6. Hamer, Victor; Dupont, Pierre. Joint optimization of predictive performance and selection stability. In: ESANN 2020 - Proceedings. Vol. 1, no.1, p. 381-386 (2020). 2020 xxx. http://hdl.handle.net/2078.1/236855

7. Valy, Dona; Verleysen, Michel; Chhun, Sophia. Data Augmentation and Text Recognition on Khmer Historical Manuscripts. 2020 xxx. http://hdl.handle.net/2078.1/258306

8. Hamer, Victor; Dupont, Pierre. Explicit Control of Feature Relevance and Selection Stability Through Pareto Optimality. In: CEUR Workshop Proceedings. Vol. 2444, no.1, p. 64-79 (2019). CEUR, 2019 xxx. http://hdl.handle.net/2078.1/220044

9. Massart, Estelle; Hendrickx, Julien; Absil, Pierre-Antoine. Curvature of the Manifold of Fixed-Rank Positive-Semidefinite Matrices Endowed with the Bures–Wasserstein Metric. In: Lecture Notes in Computer Science : Geometric Science of Information (Geometric Science of information), Frank Nielsen, Frédéric Barbaresco Eds. 2019, 9783030269791, p. 739-748 xxx. doi:10.1007/978-3-030-26980-7_77. http://hdl.handle.net/2078.1/218981

10. Renard, Emilie; Absil, Pierre-Antoine; Gallivan, Kyle A.. Minimax center to extract a common subspace from multiple datasets. In: ESANN 2019 Proceedings, 2019, 978-287-587-065-0, p. 275-280 xxx. http://hdl.handle.net/2078.1/218835

11. Dong, Shuyu; Absil, Pierre-Antoine; Gallivan, Kyle A.. Preconditioned conjugate gradient algorithms for graph regularized matrix completion. In: ESANN 2019 Proceedings, 2019, 978-287-587-065-0, p. 239-244 xxx. http://hdl.handle.net/2078.1/218834

12. Nguyen, Thanh Son; Gousenbourger, Pierre-Yves; Massart, Estelle; Absil, Pierre-Antoine. Online balanced truncation for linear time-varying systems using continuously differentiable interpolation on Grassmann manifold. In: 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), IEEE, 2019, 9781728105215, p. 165-170 xxx. doi:10.1109/codit.2019.8820675. http://hdl.handle.net/2078.1/219847

13. de Smet, Dimitri; Francaux, Marc; Baijot, Laurent; Verleysen, Michel. MAP Best Performances Prediction for Endurance Runners. 2019 xxx. http://hdl.handle.net/2078.1/258307

14. Hamer, Victor; Dupont, Pierre. Learning Computationally Efficient Metrics for Large Scale Person Identification. In: Proceedings of the Annual Machine Learning Conference of Belgium and the Netherlands 2018. Vol. /, no./, p. / (2018). 2018 xxx. http://hdl.handle.net/2078.1/204660

15. Renard, Emilie; Gallivan, Kyle A.; Absil, Pierre-Antoine. A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction. In: Latent Variable Analysis and Signal Separation : Lecture Notes in Computer Science, Springer International Publishing, 2018, 9783319937632, p. 69-78 xxx. doi:10.1007/978-3-319-93764-9_7. http://hdl.handle.net/2078.1/206910

16. Dong, Shuyu; Absil, Pierre-Antoine; Gallivan, Kyle. Graph learning for regularized low-rank matrix completion. In: MTNS 2018. p. 460-467 (2018). 2018 xxx. http://hdl.handle.net/2078.1/201674

17. Valy, Dona; Verleysen, Michel; Chhun, Sophea; Burie, Jean-Christophe. A New Khmer Palm Leaf Manuscript Dataset for Document Analysis and Recognition - SleukRith Set. 2017 xxx. http://hdl.handle.net/2078.1/197287

18. Valy, Dona; Verleysen, Michel; SOK, Kimheng. Line Segmentation for Grayscale Text Images of Khmer Palm Leaf Manuscripts. 2017 xxx. http://hdl.handle.net/2078.1/197283

19. Gousenbourger, Pierre-Yves; Massart, Estelle; Musolas, Antoni; Absil, Pierre-Antoine; Hendrickx, Julien; Jacques, Laurent; Marzouk, Youssef. Piecewise-Bezier C1 smoothing on manifolds with application to wind field estimation. In: 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017), 2017, 978-287587039-1, 305-3010 xxx. http://hdl.handle.net/2078.1/186413

20. Dong, Shuyu; Thanou, Dorina; Absil, Pierre-Antoine; Frossard, Pascal. Learning sparse models of diffusive graph signals. In: Computational Intelligence and Machine learning, 2017, 978-287587039-1, p. 251-256 xxx. http://hdl.handle.net/2078.1/192504

21. Renard, Emilie; Absil, Pierre-Antoine. Comparison of location-scale and matrix factorization batch effect removal methods on gene expression datasets. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017, 978-1-5090-3050-7, p. 1511-1518 xxx. http://hdl.handle.net/2078.1/189452

22. Branders, Vincent; Schaus, Pierre; Dupont, Pierre. Mining a sub-matrix of maximal sum. In: Proceedings of the 6th International Workshop on New Frontiers in Mining Complex Patterns in conjunction with ECML-PKDD 2017. 2017 xxx. http://hdl.handle.net/2078.1/189737

23. Gousenbourger, Pierre-Yves; Jacques, Laurent; Absil, Pierre-Antoine. Fast Method to Fit a C1 Piecewise-Bézier Function to Manifold-Valued Data Points: How Suboptimal is the Curve Obtained on the Sphere S2?. In: Geometric Science of Information. GSI 2017. Lecture Notes in Computer Science, Springer International, 2017, 978-3-319-68445-1 xxx. doi:10.1007/978-3-319-68445-1_69. http://hdl.handle.net/2078.1/189233

24. Valy, Dona; Verleysen, Michel; Sok, Kimheng. Line Segmentation Approach for Ancient Palm Leaf Manuscripts using Competitive Learning Algorithm. 2016 xxx. http://hdl.handle.net/2078.1/197296

25. Degeest, Alexandra; Verleysen, Michel; Frénay, Benoît. Feature Ranking in Changing Environments where New Features are Introduced. In: Proceedings of IJCNN 2015, IEEE, 2015, 978-1-4799-1959-8/15, 1-8 xxx. doi:10.1109/IJCNN.2015.7280533; 10.1109/IJCNN.2015.7280533. http://hdl.handle.net/2078.1/171351

26. Branders, Samuel; Frenay, Benoît; Dupont, Pierre. Survival Analysis with Cox Regression and Random Non-linear Projections. In: Proceedings of the 23th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2015 xxx. http://hdl.handle.net/2078.1/162837

27. Peluffo Ordoñez, Diego Hernan; Lee, John Aldo; Verleysen, Michel; Rodriguez, José L.; Castellanos-Dominguez, German. Unsupervised relevance analysis for feature extraction and selection. A distance-based approach for feature relevance. 2015 xxx. http://hdl.handle.net/2078.1/171343

28. Peluffo-Ordonez, Diego H.; Alvarado-Perez, Juan C.; Lee, John Aldo; Verleysen, Michel. Geometrical homotopy for data visualization. In: Proceedings of ESANN 2015, i6doc.com publ. 2015, 978-287587014-8, 525-530 xxx. http://hdl.handle.net/2078.1/171350

29. Billiet, Lieven; Hunyadi, Borbala; Matic, Vladimir; Van Huffel, Sabine; Verleysen, Michel. Single trial classification in Mobile BCI - A multiway Kernel approach. In: Proceedings of BIOSIGNALS 2015, SciTePress, 2015, 978-989-758-069-7, 5-11 xxx. doi:10.5220/0005163000050011; 10.5220/0005163000050011. http://hdl.handle.net/2078.1/171366

30. Chuor, Porchourng; Verleysen, Michel; Valy, Dona. Khmer Optical Character Recognition Using Zernike Moment. 2015, 1-6 xxx. http://hdl.handle.net/2078.1/171348

31. Eirola, E.; Lendasse, Amaury; Corona, F.; Verleysen, Michel. The delta test: The 1-NN estimator as a feature selection criterion. In: International Joint Conference on Neural Networks (IJCNN), 2014, 978-1-4799-6627-1 xxx. doi:10.1109/IJCNN.2014.6889560; 10.1109/IJCNN.2014.6889560. http://hdl.handle.net/2078.1/156924

32. Paul, Jérôme; Dupont, Pierre. Statistically interpretable importance indices for Random Forests. 2014 xxx. http://hdl.handle.net/2078.1/147350

33. Diaz, Ignacio; Cuadrado, Abel A.; Pérez, Daniel; Garcia, Francisco J.; Verleysen, Michel. Interactive Dimensionality Reduction for Visual Analytics. In: Proceedings of ESANN 2014, i6doc.com publ. 2014, 978-287419095-7, 183-188 xxx. http://hdl.handle.net/2078.1/171344

34. Lee, John Aldo; Verleysen, Michel. Two key properties of dimensionality reduction methods. In: Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014), IEEE, 2014, 978-1-4799-4518-4, 163-170 xxx. doi:10.1109/CIDM.2014.7008663; 10.1109/CIDM.2014.7008663. http://hdl.handle.net/2078.1/156909

35. Peluffo Ordoñez, Diego Hernan; Lee, John Aldo; Verleysen, Michel. Recent methods for dimensionality reduction: A brief comparative analysis. In: Proceedings of ESANN 2014, i6doc.com publ. 2014, 978-287419095-7, 189-194 xxx. http://hdl.handle.net/2078.1/171353

36. Lee, John Aldo; Peluffo Ordoñez, Diego Hernan; Verleysen, Michel. Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction. In: Proceedings of ESANN 2014, i6doc.com publ. 2014, 978-287419095-7, 177-182 xxx. http://hdl.handle.net/2078.1/171354

37. Peluffo Ordoñez, Diego Hernan; Lee, John Aldo; Verleysen, Michel. Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. In: Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2014), IEEE, 2014, 978-1-4799-4518-4, 171-177 xxx. doi:10.1109/CIDM.2014.7008664; 10.1109/CIDM.2014.7008664. http://hdl.handle.net/2078.1/156913

38. Paul, Jérôme; Dupont, Pierre. Kernel methods for mixed feature selection. In: ESANN2014, 22th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, 2014, 9782874190957, 301-306 xxx. http://hdl.handle.net/2078.1/140532

39. Frénay, Benoît; Hofmann, Daniela; Schulz, Alexander; Biehl, Michael; Hammer, Barbara. Valid Interpretation of Feature Relevance for Linear Data Mappings. 2014, 978-1-4799-4518-4 xxx. http://hdl.handle.net/2078.1/156598

40. Lombardi, Michèle; Schaus, Pierre. Cost impact guided LNS. Springer, 2014, Vol. 8451, p. 293-300 (2014) xxx. doi:10.1007/978-3-319-07046-9_21. http://hdl.handle.net/2078.1/141324

41. Dessy, Adrien; Dupont, Pierre. Computationally Efficient Test for Gene Set Dysregulation. 2014 xxx. http://hdl.handle.net/2078.1/151690

42. Degeest, Alexandra; Frénay, Benoît; Verleysen, Michel. Automatic Correction of SVM for Drifted Data Classification. In: Proceedings de la 14 ème conférence Extraction et Gestion des Connaissances (EGC 2014), 2014 xxx. http://hdl.handle.net/2078.1/138448

43. Bui, Quoc Trung; Pham, Quang Dung; Deville, Yves. Solving the quorumcast routing problem as a mixed integer program. 2014 xxx. doi:10.1007/978-3-319-07046-9_4. http://hdl.handle.net/2078.1/140937

44. Dejemeppe, Cyrille; Deville, Yves. Continuously degrading resource and interval dependent activity durations in nuclear medicine patient scheduling. 2014 xxx. doi:10.1007/978-3-319-07046-9_20. http://hdl.handle.net/2078.1/140940

45. Mairy, Jean-Baptiste; Deville, Yves; Lecoutre, Christophe. Domain k-Wise Consistency Made as Simple as Generalized Arc Consistency. 2014 xxx. doi:10.1007/978-3-319-07046-9_17. http://hdl.handle.net/2078.1/140932

46. Deville, Yves; Wouters, Pascale. Pédagogie active pour l’apprentissage de la programmation. 2014 xxx. http://hdl.handle.net/2078.1/140942

47. Paul, Jérôme; Verleysen, Michel; Dupont, Pierre. Identification of Statistically Significant Features from Random Forests. 2013 xxx. http://hdl.handle.net/2078.1/133615

48. Feraud, Baptiste; Govaerts, Bernadette; Verleysen, Michel. Assessing the repeatability and statistical advantages of homonuclear 2D-NMR spectra: an innovative clustering approach. 2013 xxx. http://hdl.handle.net/2078.1/134423

49. Feraud, Baptiste; de Tullio, Pascal; Govaerts, Bernadette; Verleysen, Michel. Assessing the repeatability and statistical advantages of homonuclear 2D-NMR spectra: a clustering approach. 2013 xxx. http://hdl.handle.net/2078.1/129972

50. Garcia-Fernandez, Francisco; Verleysen, Michel; Lee, John Aldo; Diaz, Ignacio. Stability comparison of dimensionality reduction techniques attending to data and parameters variations. 2013 xxx. http://hdl.handle.net/2078.1/141004

51. Garcia Fernandez, Francisco J.; Verleysen, Michel; Lee, John Aldo; Diaz, Ignacio. Sensitivity to parameter and data variations in dimensionality reduction techniques. In: Proceedings of the 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), i6doc.com publ.: Louvain-la-Neuve (Belgium), 2013, 978-2-87419-081-0, p. 95-100 xxx. http://hdl.handle.net/2078.1/141007

52. Bernard, Guillaume; Verleysen, Michel; Lee, John Aldo. Segmentation with Incremental Classifiers. In: Image Analysis and Processing – ICIAP 2013 (Lecture Notes in Computer Science), Springer: Berlin Heidelberg, 2013, 978-3-642-41183-0, p. 81-90 xxx. doi:10.1007/978-3-642-41184-7_9. http://hdl.handle.net/2078.1/135366

53. Verleysen, Michel; Lee, John Aldo. Nonlinear dimensionality reduction for visualization. In: Lecture Notes in Computer Science. Vol. 8226, p. 617-622 (11/2013). 2013 xxx. doi:10.1007/978-3-642-42054-2_77; 10.1007/978-3-642-42054-2_77. http://hdl.handle.net/2078.1/140947

54. Schaefer, Matthias; Zhang, Leishi; Schreck, Tobias; Tatu, Andrada; Lee, John Aldo; Verleysen, Michel; Keim, Daniel A.. Improving projection-based data analysis by feature space transformations. In: Proceedings SPIE 8654, Visualization and Data Analysis 2013, 2013 xxx. doi:10.1117/12.2000701. http://hdl.handle.net/2078.1/141012

55. Doquire, Gauthier; Frénay, Benoît; Verleysen, Michel. Risk Estimation and Feature Selection. In: Proceedings of European Symposium on Artificial Neural Networks (ESANN 2013), 2013, 161-166 xxx. http://hdl.handle.net/2078.1/138455

56. Renard, Emilie; Dupont, Pierre; Verleysen, Michel. User control for adjusting conflicting objectives in parameter-dependent visualization of data. 2013 xxx. http://hdl.handle.net/2078.1/130595

57. Frénay, Benoît; Doquire, Gauthier; Verleysen, Michel. Mutual Information: an Adequate Tool for Feature Selection. In: Proceedings of the 22nd edition of the annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2013), 2013 xxx. http://hdl.handle.net/2078.1/138452

58. Bui, Quoc Trung; Pham, Quang Dung; Deville, Yves. Solving the agricultural land allocation problem by constraint-based local search. In: Principles and Practice of Constraint Programming, Lecture Notes in Computer Science, 2013, 978-3-642-40627-0, p. 749-757 xxx. doi:10.1007/978-3-642-40627-0_55. http://hdl.handle.net/2078.1/141205

59. Massen, Florence; López-Ibáñez, Manuel; Stützle, Thomas; Deville, Yves. Experimental analysis of pheromone-based heuristic column generation using irace. In: Hybrid Metaheuristics, Lecture Notes in Computer Science, 2013, 978-3-642-38515-5, p. 92-106 xxx. doi:10.1007/978-3-642-38516-2_8. http://hdl.handle.net/2078.1/141291

60. Paul, Jérôme; Verleysen, Michel; Dupont, Pierre. The stability of feature selection and class prediction from ensemble tree classifiers. In: ESANN 2012 The 20 th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings - Bruges, Belgium from 25 to 27 April 2012 ., 2012, 978-2-87419-047-6, 263-268 xxx. http://hdl.handle.net/2078.1/113825

61. Doquire, Gauthier; Verleysen, Michel. Handling Imprecise Labels in Feature Selection with Graph Laplacian. In: Proceedings of the 2012 International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012), SciTePress, 2012, p. 162-169 xxx. doi:10.5220/0003712101620169. http://hdl.handle.net/2078.1/116778

62. Keim, Danial A.; Rossi, Fabrice; Seidl, Thomas; Verleysen, Michel; Wrobel, Stefan. Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081). In: Informatik Spectrum. Vol. 35, no.4, p. 311-317 (August 2012). Springer, 2012 xxx. doi:10.1007/s00287-012-0634-3. http://hdl.handle.net/2078.1/116816

63. Coelho, Frederico; Braga, Antonio Padua; Verleysen, Michel. Cluster homogeneity as a semi-supervised principle for feature selection using mutual information. In: Proceedings of the 20th International Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), i6doc.com, 2012, 978-2-87419-049-0, p. 507-512 xxx. http://hdl.handle.net/2078.1/116654

64. Verleysen, Michel. Information theoretic feature selection for high-dimensional data analysis. In: Proceedings of the Workshop "New Challenges in Neural Computation" (NC2), 2012 xxx. http://hdl.handle.net/2078.1/116803

65. Keim, Daniel A.; Rossi, Fabrice; Seidl, Thomas; Verleysen, Michel; Wrobel, Stefan. Information Visualization, Visual Data Mining and Machine Learning. In: Dagstuhl Reports, Dagstuhl Publishing: Germany, 2012, p. 58-83 xxx. doi:10.4230/DagRep.2.2.58; 10.4230/DagRep.2.2.58. http://hdl.handle.net/2078.1/116818

66. Bernard, Guillaume; Lee, John Aldo; Verleysen, Michel. Incremental feature computation and classification for image segmentation. In: Proceedings of the 20th International Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), i6doc.com, 2012, 978-2-87419-049-0, p. 157-162 xxx. http://hdl.handle.net/2078.1/116766

67. Verleysen, Michel. About the Optimality of Mutual Information for Feature Selection. In: Proceedings of the International Conference on Neural Information Processing (ICONIP 2012), 2012 xxx. http://hdl.handle.net/2078.1/116802

68. Doquire, Gauthier; Verleysen, Michel. A Comparison of Multivariate Mutual Information Estimators for Feature Selection. In: Proceedings of the 2012 International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012), SciTePress, 2012, p. 176-185 xxx. doi:10.5220/0003726101760185; 10.5220/0003726101760185. http://hdl.handle.net/2078.1/116769

69. Frénay, Benoît; Doquire, Gauthier; Verleysen, Michel. On the Potential Inadequacy of Mutual Information for Feature Selection. In: Proceedings of the 20th International Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), i6doc.com, 2012, 978-2-87419-049-0, p. 501-506 xxx. http://hdl.handle.net/2078.1/116666

70. Verleysen, Michel. Machine learning for high-dimensional data: the curse of dimensionality, feature selection and manifold learning. In: Proceedings of the Computational Intelligence in Healthcare summer school (CIHC 2010), 2011 xxx. http://hdl.handle.net/2078.1/91213

71. Hernandez-Lobato, Daniel; Hernandez-Lobato, José Miguel; Dupont, Pierre. Robust Multi-Class Gaussian process classification. 2011 xxx. http://hdl.handle.net/2078.1/91121

72. Verleysen, Michel. Nonlinear Dimensionality Reduction and Feature Selection. 2011 xxx. http://hdl.handle.net/2078.1/82390

73. Verleysen, Michel. Information theoretic feature selection for non-standard data. 2011 xxx. http://hdl.handle.net/2078.1/82401

74. Doquire, Gauthier; Verleysen, Michel. Graph Laplacian for Semi-supervised Feature Selection in Regression Problems. In: Advances in Computational Intelligence (Lecture Notes in Computer Science), Springer, 2011, 978-3-642-21500-1, p. 248-255 xxx. doi:10.1007/978-3-642-21501-8_31. http://hdl.handle.net/2078.1/82292

75. Guerrero-Mosquera, Carlos; Verleysen, Michel; Navia Vazquez, Angel. Dimensionality Reduction of EEG for Classification using Mutual Information and SVM. In: Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2011), IEEE, 2011, 978-1-4577-1621-8, 1-6 xxx. doi:10.1109/MLSP.2011.6064595. http://hdl.handle.net/2078.1/90793

76. Doquire, Gauthier; Verleysen, Michel. Feature Selection for Multi-label Classification Problems. In: Advances in Computational Intelligence (Lecture Notes in Computer Science), Springer, 2011, 978-3-642-21500-1, p. 9-16 xxx. doi:10.1007/978-3-642-21501-8_2. http://hdl.handle.net/2078.1/82299

77. Verleysen, Michel. Feature selection for high-dimensional data analysis. 2011 xxx. http://hdl.handle.net/2078.1/82386

78. Côme, Etienne; Cottrell, Marie; Verleysen, Michel; Lacaille, Jérôme. Aircraft Engine Fleet Monitoring Using Self-Organizing Maps and Edit Distance. In: Advances in Self-Organizing maps (Lecture notes in Computer Sciences), Springer, 2011, 978-3-642-21565-0, p. 298-307 xxx. doi:10.1007/978-3-642-21566-7_30. http://hdl.handle.net/2078.1/82272

79. Verleysen, Michel. High-dimensional data analysis: Looking for fast models ?. In: Proceedings of the International Symposium on Extreme Learning Machines (ELM 2011), 2011 xxx. http://hdl.handle.net/2078.1/116804

80. Boumal, Nicolas; Absil, Pierre-Antoine. RTRMC: A Riemannian trust-region method for low-rank matrix completion. In: Advances in Neural Information Processing Systems 24, 2011, 406-414 xxx. http://hdl.handle.net/2078.1/87419

81. Lee, John Aldo; Verleysen, Michel. Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants. In: Procedia Computer Science. Vol. 4, no. /, p. 538-547 (2011). Elsevier Ltd: [S.l.], 2011 xxx. doi:10.1016/j.procs.2011.04.056. http://hdl.handle.net/2078.1/82315

82. Lee, John Aldo; Verleysen, Michel. Unsupervised dimensionality reduction:from principal component analysis to modern nonlinear techniques. In: Proceedings des 43e Journées de Statistiques (JDS 2011), 2011 xxx. http://hdl.handle.net/2078.1/116809

83. Zakharov, Roman; Dupont, Pierre. Ensemble logistic regression for feature selection. In: Lecture Notes in Bioinformatics. no. 7036, p. 133-144 (2011). Springer: (Germany) Heidelberg, 2011 xxx. doi:10.1007/978-3-642-24855-9_12. http://hdl.handle.net/2078.1/87509

84. de Lannoy, Gaël; François, Damien; Verleysen, Michel. Class-Specific Feature Selection for One-Against-All Multiclass SVMs. In: ESANN 2011 Proceedings, i6doc.com: Louvain-le-Neuve (Belgium), 2011, 978-2-87419-044-5, p. 269-274 xxx. http://hdl.handle.net/2078.1/82355

85. Doquire, Gauthier; de Lannoy, Gaël; François, Damien; Verleysen, Michel. Feature selection for supervised inter-patient heart beat classification. In: Proceedings of the 4th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2011), SciTePress, 2011, 978-989-8425-35-5, 67-73 xxx. http://hdl.handle.net/2078.1/82378

86. Doquire, Gauthier; Verleysen, Michel. Feature selection with mutual information for uncertain data. In: Lecture Notes in Computer Science. Vol. 6862, p. 330-341 (2011). Springer-Verlag: Berlin Heidelberg, 2011 xxx. doi:10.1007/978-3-642-23544-3_25. http://hdl.handle.net/2078.1/116589

87. Hazan, Aurélien; Verleysen, Michel; Cottrell, Marie; Lacaille, Jérôme. Bayesian inference for outlier detection in vibration spectra with small learning dataset. In: Proceedings of Surveillance 6, 2011, 2011, 1-15 xxx. http://hdl.handle.net/2078.1/90781

88. Doquire, Gauthier; Verleysen, Michel. An hybrid approach to feature selection for mixed categorical and continuous data. 2011 xxx. http://hdl.handle.net/2078.1/90765

89. Verleysen, Michel. Data Visualization with Nonlinear Projections. 2011 xxx. http://hdl.handle.net/2078.1/82399

90. Frénay, Benoît; de Lannoy, Gaël; Verleysen, Michel. Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs. In: Lecture Notes in Computer Science. Vol. 6911, p. 455-470 (2011). In: Proceedings of ECML-PKDD 2011, Springer: (Germany) Heidelberg, 2011 xxx. doi:10.1007/978-3-642-23780-5. http://hdl.handle.net/2078.1/116594

91. Doquire, Gauthier; Verleysen, Michel. Mutual information for feature selection with missing data. In: Proceedings of the 19th European Symposium on Artificial Neural networks, Computational Intelligence and Machine learning (ESANN 2011), i6doc.com: Louvain-la-Neuve (Belgium), 2011, 978-2-87419-044-5, 263-268 xxx. http://hdl.handle.net/2078.1/82348

92. Doquire, Gauthier; Verleysen, Michel. Mutual information based feature selection for mixed data. In: ESANN 2011 Proceedings, i6doc.com, 2011, 978-2-87419-044-5 xxx. http://hdl.handle.net/2078.1/82340

93. HO, Trong Viet; Deville, Yves; Bonaventure, Olivier; François, Pierre. Traffic engineering for multiple spanning tree protocol in large data centers. 2011 xxx. http://hdl.handle.net/2078.1/87167

94. Massen, Florence; Deville, Yves; Van Hentenryck, Pascal. A relaxation-guided approach for vehicle routing problems with black box feasibility. 2011 xxx. http://hdl.handle.net/2078.1/87185

95. Mairy, Jean-Baptiste; Deville, Yves; Van Hentenryck, Pascal. Reinforced Adaptive Large Neighborhood Search. 2011 xxx. http://hdl.handle.net/2078.1/124303

96. Mouthuy, Sébastien; Deville, Yves; Van Hentenryck, Pascal. A multi-stage very large-scale neighborhood search for the vehicle routing problem with soft time-windows. 2011 xxx. http://hdl.handle.net/2078.1/87159

97. Deville, Yves; Van Hentenryck, Pascal; Mairy, Jean-Baptiste. Domaine consistance et valeurs interdites. 2011 xxx. http://hdl.handle.net/2078.1/87151

98. Hazan, Aurélien; Verleysen, Michel; Cottrell, Marie; Lacaille, Jérôme. Linear smoothing of FRF for aicraft engine vibration monitoring. In: Proceedings of the International Conference on Noise and vibration Engineering (ISMA 2010), 2010, p. 2857-2868 xxx. http://hdl.handle.net/2078.1/90809

99. Miché, Yoan; Eirola, Emile; Bas, Patrick; Simula, Olli; Jutten, Christian; Lendasse, Amaury; Verleysen, Michel. Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010), 2010, 2-930307-10-2, p. 19-24 xxx. http://hdl.handle.net/2078.1/90852

100. Guerrero-Mosquera, Carlos; Verleysen, Michel; Navia Vazquez, Angel. EEG Feature Selection Using Mutual Information and Support Vector Machine: A Comparative Analysis. In: Proceedings of the 32nd Annual International IEEE EMBC Conference (EMBC 2010), 2010, p. 4946-4949 xxx. http://hdl.handle.net/2078.1/90821

101. Co circ me, E.; Cottrell, M.; Verleysen, Michel; Lacaille, J.. Aircraft Engine Health Monitoring Using Self-organizing Maps. In: Advances in Data Mining Applications and Theoretical Aspects. 10th Industrial Conference, ICDM 2010, Springer verlag, 2010, 978-3-642-14399-1, p. 405-417 xxx. doi:10.1007/978-3-642-14400-4_31. http://hdl.handle.net/2078.1/67366

102. Walkinshaw, Neil; Bogdanov, Kirill; Damas, Christophe; Lambeau, Bernard; Dupont, Pierre. A framework for the competitive evaluation of model inference techniques. In: Proceedings of the First International Workshop on Model Inference In Testing, ACM: New York, USA, 2010, 978-1-4503-0147-3, p. 1-9 xxx. doi:10.1145/1868044.1868045. http://hdl.handle.net/2078.1/87504

103. Verleysen, Michel. Machine learning for high-dimensional data. In: Proceedings of Artificial Intelligence and Applications (AIA 2010), 2010 xxx. http://hdl.handle.net/2078.1/91220

104. Hazan, Aurélien; Verleysen, Michel; Cottrell, Marie; Lacaille, Jérôme. Trajectory Clustering for Vibration Detection in Aircraft Engines. In: Lecture Notes in Computer Science. no. 6171, p. 362-375. Springer: (Germany) Heidelberg, 2010 xxx. http://hdl.handle.net/2078.1/90536

105. Hernandez-Lobato, Daniel; Hernández-Lobato, José Miguel; Helleputte, Thibault; Dupont, Pierre. Expectation Propagation for Bayesian Multi-task Feature Selection. In: Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010 (Lecture notes in artificial intellgience), Springer: (Germany) Heidelberg, 2010, 978-3-642-15879-7, 522-537 xxx. http://hdl.handle.net/2078.1/67341

106. Lee, John Aldo; Verleysen, Michel. Unsupervised Dimensionality Reduction: Overview and Recent Advances. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), IEEE, 2010, p. 4163-4170 xxx. http://hdl.handle.net/2078.1/90836

107. Onclinx, Victor; Lee, John Aldo; Wertz, Vincent; Verleysen, Michel. Dimensionality reduction by rank preservation. In: Proceedings of the 2010 International Joint Conference on Neural Networks (IJCNN 2010), IEEE, 2010, 978-1-4244-6916-1, 1599-1606 xxx. doi:10.1109/IJCNN.2010.5596347. http://hdl.handle.net/2078.1/68553

108. Wismueller, Axel; Verleysen, Michel; Aupetit, Michael; Lee, John Aldo. Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010), 2010, p. 71-80 xxx. http://hdl.handle.net/2078.1/90884

109. Lee, John Aldo; Verleysen, Michel. On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding. In: Proceedings of the 19th International Conference on Computational Statistics (COMPSTAT 2010), 2010 xxx. http://hdl.handle.net/2078.1/90826

110. Verleysen, Michel; Lee, John Aldo. Nonlinear dimensionality reduction. In: Proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2010), 2010 xxx. http://hdl.handle.net/2078.1/91219

111. Lee, John Aldo; Verleysen, Michel. Unsupervised dimensionality reduction: from principal component analysis to modern nonlinear techniques. In: Proceedings of ERCIM working group on Computing & Statistics (ERCIM 2010), 2010 xxx. http://hdl.handle.net/2078.1/82396

112. Frénay, Benoît; Verleysen, Michel. Using SVMs with randomised feature spaces: an extreme learning approach. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010), 2010, p. 315-320 xxx. http://hdl.handle.net/2078.1/90878

113. de Lannoy, Gaël; François, Damien; Delbeke, Jean; Verleysen, Michel. Feature relevance assessment in automatic inter-patient heart beat classification. In: Proceedings of the 3rd International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2010), 2010, p. 13-20 xxx. http://hdl.handle.net/2078.1/90890

114. De Decker, Arnaud; Lee, John Aldo; François, Damien; Verleysen, Michel. Mode Estimation in High-dimensional Spaces with Flat-top Kernels: Application to Image Denoising. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010), d-side publi, 2010, 2-930307-10-2, p. 411-416 xxx. http://hdl.handle.net/2078.1/140944

115. Côme, Etienne; Cottrell, Marie; Verleysen, Michel; Lacaille, Jérôme. Self Organizing Star (SOS) for health monitoring. In: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010), 2010, p. 99-104 xxx. http://hdl.handle.net/2078.1/90842

116. Coelho, Frederico; Braga, Antonio Padua; Verleysen, Michel. Multi-Objective Semi-supervised Feature Selection and Model Selection based on Pearson's Correlation Coefficient. In: Lecture Notes in Computer Science. no. 6419, p. 509-516. Springer: (Germany) Heidelberg, 2010 xxx. http://hdl.handle.net/2078.1/90531

117. Dupuis, Julien; Schaus, Pierre; Deville, Yves. Consistency Check for the Bin Packing Constraint Revisited. In: Integration of AI and OR Techniques in Constraint Programming for Cominatorial Optimization Problems. 7th International Conference, CPAIOR 2010, Springer, 2010, 978-3-642-13519-4, p. 117-122 xxx. doi:10.1007/978-3-642-13520-0_15. http://hdl.handle.net/2078.1/67393

118. Deville, Yves; Van Hentenryck, Pascal. Domain consistency with forbidden values. 2010 xxx. http://hdl.handle.net/2078.1/87138

119. Pham, Quang Dung; Deville, Yves; Do, Phan-Thuan; Ho, Tuong Vinh. Constraint-based local search for solving non-simple paths problems on graphs: application to the routing for network covering problem. In: Proceedings of the 2010 Symposium on Information and Communication Technology, 2010, 978-1-4503-0105-3, p. 1-8 xxx. http://hdl.handle.net/2078.1/87134

120. Dupuis, Julien; Schaus, Pierre; Deville, Yves. Vérification de consistence pour la constrainte de bin packing. 2010 xxx. http://hdl.handle.net/2078.1/86173

121. Schaus, Pierre; Van Hentenryck, Pascal; Monette, Jean-Noël; Coffrin, Carleton; Michel, Laurent; Deville, Yves. Solving steel mill slab problems with constraint-based techniques: CP, LNS, and CBLS. In: Constraints : an international journal. Vol. 16, no. 2, p. 125-147 (2011). Springer New York LLC: (United States) New York, 2010 xxx. doi:10.1007/s10601-010-9100-5. http://hdl.handle.net/2078.1/87149

122. Pham, Quang Dung; Deville, Yves; Van Hentenryck, Pascal. Constraint-based Local Search for Constrained Optimum Paths Problems. In: Integration of AI and OR Techniques in Constraint Programming for Cominatorial Optimization Problems. 7th International Conference, CPAIOR 2010, Springer, 2010, 978-3-642-13519-4, p. 234-248 xxx. http://hdl.handle.net/2078.1/67392

123. Mairy, Jean-Baptiste; Schaus, Pierre; Deville, Yves. Generic adaptive heuristics for large neighborhood search. 2010 xxx. http://hdl.handle.net/2078.1/87135


Book Chapters


1. Derval, Guillaume; Branders, Vincent; Dupont, Pierre; Schaus, Pierre. The Maximum Weighted Submatrix Coverage Problem: A CP Approach. In: Integration of Constraint Programming, Artificial Intelligence, and Operations Research : Lecture Notes in Computer Science (Lecture Notes in Computer Science; xxx), Springer, Cham, 2019, p. 258-274. 978-3-030-19212-9. xxx xxx. doi:10.1007/978-3-030-19212-9_17. http://hdl.handle.net/2078.1/218893

2. Yuan, Xinru; Huang, Wen; Absil, Pierre-Antoine; Gallivan, Kyle A.. Averaging Symmetric Positive-Definite Matrices. In: Hanbook of Variational Methods for Nonlinear Geometric Data and applications , Springer handbooks, 2019, p. 555-575. 978-3-030-31350-0. xxx xxx. doi:10.1007/978-3-030-31351-7_20. http://hdl.handle.net/2078.1/229421

3. Branders, Vincent; Schaus, Pierre; Dupont, Pierre. Combinatorial Optimization Algorithms to Mine a Sub-Matrix of Maximal Sum. In: New Frontiers in Mining Complex Patterns (Lecture notes in computer science; xxx), xxx, 2018, p. 65-79. 978-3-319-78679-7. xxx xxx. doi:10.1007/978-3-319-78680-3_5. http://hdl.handle.net/2078.1/196614

4. Peluffo Ordoñez, Diego Hernan; Lee, John Aldo; Verleysen, Michel; Alvarado-Pérez, Juan C.. Geometrical homotopy for data visualization. In: ESANN 2015 - 23rd Eur. Symp. on Artificial Neural Networks, Computational Intelligence and Machine Learning , D-side: Bruges, 2015, p. 525-530. 978-2-87587-014-8. xxx xxx. http://hdl.handle.net/2078.1/168996

5. Doquire, Gauthier; Verleysen, Michel. A Performance Evaluation of Mutual Estimators for Multivariate Feature Selection. In: Pattern Recognition - Applications and Methods (Advances in Intelligent Systems and Computing; xxx), Springer-Verlag: Berlin-Heidelberg, 2013, p. 51-63. 978-3-642-36529-4. xxx xxx. doi:10.1007/978-3-642-36530-0_5. http://hdl.handle.net/2078.1/157006

6. Lee, John Aldo; Verleysen, Michel. Graph-Based Dimensionality Reduction. In: Image Processing and Analysis with Graphs: Theory and Practice , CRC Press, 2012, p. 351-382. 978-1-4398-5507-2. xxx xxx. http://hdl.handle.net/2078.1/116530

7. Milgrom, Elie; Deville, Yves. L'informatique en FSA / à l'EPL. In: Des Écoles Spéciales à l'EPL 50 ans de science et de technologie à l'UCL , xxx, 2012. 978-2-87558-092-4. xxx xxx. http://hdl.handle.net/2078.1/141306

8. François, Damien; Wertz, Vincent; Verleysen, Michel. Choosing the Metric: A Simple Model Approach. In: Meta-Learning in Computational Intelligence (Studies in Computational Intelligence; xxx), Springer, 2011, p. 97-115. 978-3-642-20979-6. xxx xxx. doi:10.1007/978-3-642-20980-2_3. http://hdl.handle.net/2078.1/82257

9. de Lannoy, Gaël; François, Damien; Delbeke, Jean; Verleysen, Michel. Weighted SVMs and Feature Relevance Assessment in Supervised Heart Beat Classification.. In: Biomedical Engineering Systems and Technologies: Third International Joint Conference, BIOSTEC 2010, Valencia, Spain, January 20-23, 2010, Revised Selected Papers (Communications in Computer and Information Science; xxx), Springer-Verlag: (Germany) Berlin, 2011, p. 212-223. 978-3-642-18471-0. xxx xxx. doi:10.1007/978-3-642-18472-7_17. http://hdl.handle.net/2078.1/111099

10. Journée, M.; Bach, F.H.; Absil, Pierre-Antoine; Sepulchre, Rodolphe. Refining Sparse Principal Components. In: Recent Advances in Optimization and its Applications in Engineering , Springer: Berlin Heidelberg, 2010, p. 165-171. 978-3-642-12597-3. xxx xxx. doi:10.1007/978-3-642-12598-0_14. http://hdl.handle.net/2268/78592 ; http://hdl.handle.net/2078.1/90687


Working Papers


1. Rousseau, Réjane; Feraud, Baptiste; Govaerts, Bernadette; Verleysen, Michel. Combination of Independent Component Analysis and statistical modelling for the identification of metabonomic biomarkers in 1H-NMR spectroscopy (second version). 2013. 32 p. ISBA Discussion Paper 2013/06. http://hdl.handle.net/2078.1/126996


Books


1. Verleysen, Michel. ESANN 2021, 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2021: Proceedings. 2021. 9782875870810.pages. http://hdl.handle.net/2078.1/268447

2. Verleysen, Michel. 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2020. 978-2-87587-073-5.pages. http://hdl.handle.net/2078.1/268568

3. Verleysen, Michel. 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2019. 978-287587065-0.pages. http://hdl.handle.net/2078.1/268569

4. Verleysen, Michel. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2015: Proceedings. Michel Verleysen, 2015. 978-287587014-8. 613 pages. http://hdl.handle.net/2078.1/171365

5. Verleysen, Michel. 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine learning 2014: Proceedings. Michel Verleysen, 2014. 978-287419095-7. 730 pages. http://hdl.handle.net/2078.1/171363

6. Borgelt, C.; Gil, Maria Angeles; Souza, Joao M.C.; Verleysen, Michel. Towards Advanced Data Analysis by Combining Soft Computing and Statistics. Springer: Berlin, 2013. 978-3-642-30277-0. 378 pages. http://hdl.handle.net/2078.1/116798

7. Verleysen, Michel. 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Proceedings. i6doc.com: Louvain-la-Neuve (Belgium), 2013. 978-2-8741-9081-0. 598 pages. http://hdl.handle.net/2078.1/142256

8. Verleysen, Michel. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2012: Proceedings. i6doc.com, 2012. 978-2-87419-049-0. 664 pages. http://hdl.handle.net/2078.1/116801

9. Verleysen, Michel. ESANN 2011, 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2011: Proceedings. i6doc.com: Louvain-la-Neuve (Belgium), 2011. 978-2-87419-044-5. 509 pages. http://hdl.handle.net/2078.1/82383

10. Verleysen, Michel. 18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2010: Proceedings. d-side publ.: Evere (Belgium), 2010. 2-930307-10-2. 568 pages. http://hdl.handle.net/2078.1/91193