All 'machine learning and artificial intelligence' publications


Journal Articles


1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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


Conference Papers


1. 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). http://hdl.handle.net/2078.1/204660

2. 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. http://hdl.handle.net/2078.1/186413

3. 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. doi:10.1007/978-3-319-68445-1_69. http://hdl.handle.net/2078.1/189233

4. 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. http://hdl.handle.net/2078.1/189452

5. 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. http://hdl.handle.net/2078.1/192504

6. 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. http://hdl.handle.net/2078.1/189737

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

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

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

10. 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. doi:10.5220/0005163000050011; 10.5220/0005163000050011. http://hdl.handle.net/2078.1/171366

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

12. 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. http://hdl.handle.net/2078.1/162837

13. 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. doi:10.1109/IJCNN.2015.7280533; 10.1109/IJCNN.2015.7280533. http://hdl.handle.net/2078.1/171351

14. 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. http://hdl.handle.net/2078.1/171350

15. 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. http://hdl.handle.net/2078.1/171343

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

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

18. 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. http://hdl.handle.net/2078.1/156598

19. 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. http://hdl.handle.net/2078.1/171344

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

21. 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. http://hdl.handle.net/2078.1/140532

22. 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. doi:10.1109/IJCNN.2014.6889560; 10.1109/IJCNN.2014.6889560. http://hdl.handle.net/2078.1/156924

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

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

25. 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. http://hdl.handle.net/2078.1/138448

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

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

28. 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. doi:10.1109/CIDM.2014.7008664; 10.1109/CIDM.2014.7008664. http://hdl.handle.net/2078.1/156913

29. 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. doi:10.1109/CIDM.2014.7008663; 10.1109/CIDM.2014.7008663. http://hdl.handle.net/2078.1/156909

30. 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. http://hdl.handle.net/2078.1/171354

31. 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. http://hdl.handle.net/2078.1/171353

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

33. 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. doi:10.1007/978-3-642-38516-2_8. http://hdl.handle.net/2078.1/141291

34. 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. http://hdl.handle.net/2078.1/138452

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

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

37. 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. http://hdl.handle.net/2078.1/138455

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

39. 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. doi:10.1007/978-3-642-40627-0_55. http://hdl.handle.net/2078.1/141205

40. 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. doi:10.1007/978-3-642-41184-7_9. http://hdl.handle.net/2078.1/135366

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

42. 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. doi:10.1117/12.2000701. http://hdl.handle.net/2078.1/141012

43. 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. http://hdl.handle.net/2078.1/141007

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

45. 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. http://hdl.handle.net/2078.1/116654

46. 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. doi:10.5220/0003712101620169. http://hdl.handle.net/2078.1/116778

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

48. 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. doi:10.5220/0003726101760185; 10.5220/0003726101760185. http://hdl.handle.net/2078.1/116769

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

50. 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. doi:10.4230/DagRep.2.2.58; 10.4230/DagRep.2.2.58. http://hdl.handle.net/2078.1/116818

51. 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. doi:10.1007/s00287-012-0634-3. http://hdl.handle.net/2078.1/116816

52. 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. http://hdl.handle.net/2078.1/116666

53. 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. http://hdl.handle.net/2078.1/113825

54. 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. http://hdl.handle.net/2078.1/116766

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

56. 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. doi:10.1007/978-3-642-24855-9_12. http://hdl.handle.net/2078.1/87509

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

58. 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. http://hdl.handle.net/2078.1/91213

59. 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. doi:10.1007/978-3-642-23544-3_25. http://hdl.handle.net/2078.1/116589

60. 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. doi:10.1007/978-3-642-21501-8_2. http://hdl.handle.net/2078.1/82299

61. 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. http://hdl.handle.net/2078.1/87419

62. 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. doi:10.1109/MLSP.2011.6064595. http://hdl.handle.net/2078.1/90793

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

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

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

66. 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. http://hdl.handle.net/2078.1/90781

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

68. 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. http://hdl.handle.net/2078.1/82378

69. 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. doi:10.1007/978-3-642-21501-8_31. http://hdl.handle.net/2078.1/82292

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

71. 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. doi:10.1007/978-3-642-23780-5. http://hdl.handle.net/2078.1/116594

72. 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. http://hdl.handle.net/2078.1/82348

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

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

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

76. 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. doi:10.1007/978-3-642-21566-7_30. http://hdl.handle.net/2078.1/82272

77. 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. http://hdl.handle.net/2078.1/82355

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

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

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

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. 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. http://hdl.handle.net/2078.1/116809

83. 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. http://hdl.handle.net/2078.1/87134

84. 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. http://hdl.handle.net/2078.1/67392

85. 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. doi:10.1145/1868044.1868045. http://hdl.handle.net/2078.1/87504

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

87. 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. doi:10.1007/978-3-642-13520-0_15. http://hdl.handle.net/2078.1/67393

88. 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. http://hdl.handle.net/2078.1/90878

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

90. 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. http://hdl.handle.net/2078.1/90890

91. 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. http://hdl.handle.net/2078.1/90842

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

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

94. 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. http://hdl.handle.net/2078.1/90531

95. 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. http://hdl.handle.net/2078.1/90536

96. 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. http://hdl.handle.net/2078.1/67341

97. 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. http://hdl.handle.net/2078.1/90809

98. 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. http://hdl.handle.net/2078.1/90821

99. 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. doi:10.1007/s10601-010-9100-5. http://hdl.handle.net/2078.1/87149

100. 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. doi:10.1007/978-3-642-14400-4_31. http://hdl.handle.net/2078.1/67366

101. 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. http://hdl.handle.net/2078.1/90852

102. 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. http://hdl.handle.net/2078.1/90836

103. 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. http://hdl.handle.net/2078.1/90826

104. 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. http://hdl.handle.net/2078.1/90884

105. 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. http://hdl.handle.net/2078.1/91219

106. 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. http://hdl.handle.net/2078.1/140944

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. doi:10.1109/IJCNN.2010.5596347. http://hdl.handle.net/2078.1/68553

108. 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. http://hdl.handle.net/2078.1/82396


Book Chapters


1. 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. doi:10.1007/978-3-319-78680-3_5. http://hdl.handle.net/2078.1/196614

2. 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. http://hdl.handle.net/2078.1/168996

3. 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. doi:10.1007/978-3-642-36530-0_5. http://hdl.handle.net/2078.1/157006

4. 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. http://hdl.handle.net/2078.1/141306

5. 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. http://hdl.handle.net/2078.1/116530

6. 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. doi:10.1007/978-3-642-20980-2_3. http://hdl.handle.net/2078.1/82257

7. 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. doi:10.1007/978-3-642-18472-7_17. http://hdl.handle.net/2078.1/111099

8. 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. 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) (xxx), 2013. 32 p. http://hdl.handle.net/2078.1/126996


Books


1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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