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ORCIDMichel Verleysen
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- affiliation: Université catholique de Louvain, Belgium
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2020 – today
- 2024
[j81]Edouard Couplet, Pierre Lambert
, Michel Verleysen, John A. Lee, Cyril de Bodt:
Investigating latent representations and generalization in deep neural networks for tabular data. Neurocomputing 597: 127967 (2024)- 2023
- [j80]Stef van den Elzen, Gennady L. Andrienko, Natalia V. Andrienko, Brian D. Fisher, Rafael Messias Martins, Jaakko Peltonen, Alexandru C. Telea, Michel Verleysen:
The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications. IEEE Computer Graphics and Applications 43(2): 78-88 (2023) - [j79]Walter Serna-Serna, Cyril de Bodt, Andrés Marino Álvarez-Meza, John A. Lee, Michel Verleysen, Álvaro Ángel Orozco-Guitiérrez:
Semi-supervised t-SNE with multi-scale neighborhood preservation. Neurocomputing 550: 126496 (2023) - [c176]Edouard Couplet, Pierre Lambert, Michel Verleysen, John A. Lee, Cyril de Bodt:
On the number of latent representations in deep neural networks for tabular data. ESANN 2023 - [i18]Reza Sameni, Frédéric Vrins, Fabienne Parmentier, Christophe Hérail, Vincent Vigneron, Michel Verleysen, Christian Jutten, Mohammad B. Shamsollahi:
Electrode Selection for Noninvasive Fetal Electrocardiogram Extraction using Mutual Information Criteria. CoRR abs/2302.00206 (2023) - 2022
- [j78]Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee:
SQuadMDS: A lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP. Neurocomputing 503: 17-27 (2022) - [j77]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John Aldo Lee:
Fast Multiscale Neighbor Embedding. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1546-1560 (2022) - [i17]Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee:
SQuadMDS: a lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP. CoRR abs/2202.12087 (2022) - 2021
- [j76]Alexandra Degeest, Benoît Frénay, Michel Verleysen:
Reading grid for feature selection relevance criteria in regression. Pattern Recognit. Lett. 148: 92-99 (2021) - [c175]Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee:
Stochastic quartet approach for fast multidimensional scaling. ESANN 2021 - [c174]Pierre Lambert, John A. Lee, Michel Verleysen, Cyril de Bodt:
Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding. ESANN 2021 - 2020
- [j75]Dounia Mulders, Cyril de Bodt, Johannes Bjelland, Alex Pentland, Michel Verleysen, Yves-Alexandre de Montjoye:
Inference of node attributes from social network assortativity. Neural Comput. Appl. 32(24): 18023-18043 (2020) - [j74]Frederico Coelho, Marcelo Costa, Michel Verleysen, Antônio P. Braga:
LASSO multi-objective learning algorithm for feature selection. Soft Comput. 24(17): 13209-13217 (2020) - [c173]Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu:
Perplexity-free Parametric t-SNE. ESANN 2020: 387-392 - [c172]Dona Valy, Michel Verleysen, Sophea Chhun:
Data Augmentation and Text Recognition on Khmer Historical Manuscripts. ICFHR 2020: 73-78 - [c171]Michel Verleysen:
Machine Learning with Limited Size Datasets. IJCCI 2020: 11 - [c170]Michel Verleysen:
Machine Learning with Limited Size Datasets. PECCS 2020: 5 - [i16]Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu:
Perplexity-free Parametric t-SNE. CoRR abs/2010.01359 (2020)
2010 – 2019
- 2019
- [j73]Frederico Coelho, Cristiano Leite Castro, Antônio P. Braga, Michel Verleysen:
Semi-supervised relevance index for feature selection. Neural Comput. Appl. 31(S-2): 989-997 (2019) - [j72]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John Aldo Lee:
Nonlinear Dimensionality Reduction With Missing Data Using Parametric Multiple Imputations. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1166-1179 (2019) - [c169]Cyril de Bodt, Dounia Mulders, Daniel López Sánchez, Michel Verleysen, John A. Lee:
Class-aware t-SNE: cat-SNE. ESANN 2019 - [c168]Ángel Campo, Marc Francaux, Laurent Baijot, Michel Verleysen:
MAP best performances prediction for endurance runners. ESANN 2019 - [c167]Dounia Mulders, Cyril de Bodt, Nicolas Lejeune, John A. Lee, André Mouraux, Michel Verleysen:
Tensor factorization to extract patterns in multimodal EEG data. ESANN 2019 - [c166]Alexandra Degeest, Michel Verleysen, Benoît Frénay:
Comparison Between Filter Criteria for Feature Selection in Regression. ICANN (2) 2019: 59-71 - [c165]Dona Valy, Michel Verleysen, Sophea Chhun:
Text Recognition on Khmer Historical Documents using Glyph Class Map Generation with Encoder-Decoder Model. ICPRAM 2019: 749-756 - [c164]Alexandra Degeest, Michel Verleysen, Benoît Frénay:
About Filter Criteria for Feature Selection in Regression. IWANN (2) 2019: 579-590 - 2018
- [j71]Made Windu Antara Kesiman, Dona Valy, Jean-Christophe Burie, Erick Paulus, Mira Suryani, Setiawan Hadi, Michel Verleysen, Sophea Chhun, Jean-Marc Ogier:
Benchmarking of Document Image Analysis Tasks for Palm Leaf Manuscripts from Southeast Asia. J. Imaging 4(2): 43 (2018) - [c163]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee:
Perplexity-free t-SNE and twice Student tt-SNE. ESANN 2018 - [c162]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee:
Extensive assessment of Barnes-Hut t-SNE. ESANN 2018 - [c161]Dounia Mulders, Cyril de Bodt, Nicolas Lejeune, André Mouraux, Michel Verleysen:
Spatial Filtering of EEG Signals to Identify Periodic Brain Activity Patterns. LVA/ICA 2018: 524-533 - [c160]Dona Valy, Michel Verleysen, Sophea Chhun, Jean-Christophe Burie:
Character and Text Recognition of Khmer Historical Palm Leaf Manuscripts. ICFHR 2018: 13-18 - [c159]Made Windu Antara Kesiman, Dona Valy, Jean-Christophe Burie, Erick Paulus, Mira Suryani, Setiawan Hadi, Michel Verleysen, Sophea Chhun, Jean-Marc Ogier:
ICFHR 2018 Competition On Document Image Analysis Tasks for Southeast Asian Palm Leaf Manuscripts. ICFHR 2018: 483-488 - [c158]Dounia Mulders, Cyril de Bodt, Nicolas Lejeune, André Mouraux, Michel Verleysen:
Linear Periodic Discriminant Analysis of Multidimensional Signals. ICONIP (6) 2018: 476-487 - [c157]Alexandra Degeest, Michel Verleysen, Benoît Frénay:
Smoothness Bias in Relevance Estimators for Feature Selection in Regression. AIAI 2018: 285-294 - 2017
- [j70]Andrés Marino Álvarez-Meza, John Aldo Lee, Michel Verleysen, Germán Castellanos-Domínguez:
Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity. Neurocomputing 222: 36-46 (2017) - [j69]Mohamed Khalil El Mahrsi, Etienne Côme, Latifa Oukhellou, Michel Verleysen:
Clustering Smart Card Data for Urban Mobility Analysis. IEEE Trans. Intell. Transp. Syst. 18(3): 712-728 (2017) - [c156]Dona Valy, Michel Verleysen, Sophea Chhun, Jean-Christophe Burie:
A New Khmer Palm Leaf Manuscript Dataset for Document Analysis and Recognition: SleukRith Set. HIP@ICDAR 2017: 1-6 - [c155]Dimitri de Smet, Michel Verleysen, Marc Francaux:
Running Race Times Prediction and Runner Performances Comparison using a Matrix Factorization Approach. icSPORTS 2017: 96-101 - [c154]Dona Valy, Michel Verleysen, Kimheng Sok:
Line segmentation for grayscale text images of khmer palm leaf manuscripts. IPTA 2017: 1-6 - [c153]Dounia Mulders, Cyril de Bodt, Johannes Bjelland, Alex 'Sandy' Pentland, Michel Verleysen, Yves-Alexandre de Montjoye:
Improving individual predictions using social networks assortativity. WSOM 2017: 169-176 - 2016
- [j68]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
A Mutual Information estimator for continuous and discrete variables applied to Feature Selection and Classification problems. Int. J. Comput. Intell. Syst. 9(4): 726-733 (2016) - [j67]Benoît Frénay, Michel Verleysen:
Reinforced Extreme Learning Machines for Fast Robust Regression in the Presence of Outliers. IEEE Trans. Cybern. 46(12): 3351-3363 (2016) - [c152]Ignacio Díaz Blanco, Abel Alberto Cuadrado Vega, Michel Verleysen:
A state-space model on interactive dimensionality reduction. ESANN 2016 - [c151]Dona Valy, Michel Verleysen, Kimheng Sok:
Line Segmentation Approach for Ancient Palm Leaf Manuscripts Using Competitive Learning Algorithm. ICFHR 2016: 108-113 - [c150]Sergio García-Vega, Germán Castellanos-Domínguez, Michel Verleysen, John Aldo Lee:
Multi-step-ahead forecasting using kernel adaptive filtering. IJCNN 2016: 2132-2139 - [c149]Dimitri de Smet, Marc Francaux, Julien M. Hendrickx, Michel Verleysen:
Heart Rate Modelling as a Potential Physical Fitness Assessment for Runners and Cyclists. MLSA@PKDD/ECML 2016 - 2015
- [j66]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental classification of objects in scenes: Application to the delineation of images. Neurocomputing 152: 45-57 (2015) - [j65]John Aldo Lee, Diego Hernán Peluffo-Ordóñez, Michel Verleysen:
Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure. Neurocomputing 169: 246-261 (2015) - [c148]Lieven Billiet, Borbála Hunyadi, Vladimir Matic, Sabine Van Huffel, Michel Verleysen, Maarten De Vos:
Single Trial Classification for Mobile BCI - A Multiway Kernel Approach. BIOSIGNALS 2015: 5-11 - [c147]Diego Hernán Peluffo-Ordóñez, Juan Carlos Alvarado-Pérez, John Aldo Lee, Michel Verleysen:
Geometrical homotopy for data visualization. ESANN 2015 - [c146]Alexandra Degeest, Michel Verleysen, Benoît Frénay:
Feature ranking in changing environments where new features are introduced. IJCNN 2015: 1-8 - [i15]Daniel A. Keim, Tamara Munzner, Fabrice Rossi, Michel Verleysen:
Bridging Information Visualization with Machine Learning (Dagstuhl Seminar 15101). Dagstuhl Reports 5(3): 1-27 (2015) - 2014
- [j64]Benoît Frénay, Gauthier Doquire, Michel Verleysen:
Estimating mutual information for feature selection in the presence of label noise. Comput. Stat. Data Anal. 71: 832-848 (2014) - [j63]Benoît Frénay, Michel Verleysen:
Pointwise probability reinforcements for robust statistical inference. Neural Networks 50: 124-141 (2014) - [j62]Benoît Frénay, Michel Verleysen:
Classification in the Presence of Label Noise: A Survey. IEEE Trans. Neural Networks Learn. Syst. 25(5): 845-869 (2014) - [c145]John Aldo Lee, Michel Verleysen:
Two key properties of dimensionality reduction methods. CIDM 2014: 163-170 - [c144]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen:
Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. CIDM 2014: 171-177 - [c143]Ludovic-Henri Gustin, François Durvaux, Stéphanie Kerckhof, François-Xavier Standaert, Michel Verleysen:
Support Vector Machines for Improved IP Detection with Soft Physical Hash Functions. COSADE 2014: 112-128 - [c142]Ignacio Díaz Blanco, Abel Alberto Cuadrado Vega, Daniel Pérez, Francisco J. García-Fernández, Michel Verleysen:
Interactive dimensionality reduction for visual analytics. ESANN 2014 - [c141]John Aldo Lee, Diego Hernán Peluffo-Ordóñez, Michel Verleysen:
Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction. ESANN 2014 - [c140]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen:
Recent methods for dimensionality reduction: A brief comparative analysis. ESANN 2014 - [c139]Alexandra Degeest, Benoît Frénay, Michel Verleysen:
Automatic correction of SVM for drifted data classification. EGC 2014: 311-316 - [c138]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen, José L. Rodríguez, Germán Castellanos-Domínguez:
Unsupervised Relevance Analysis for Feature Extraction and Selection - A Distance-based Approach for Feature Relevance. ICPRAM 2014: 310-315 - [c137]Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen:
The delta test: The 1-NN estimator as a feature selection criterion. IJCNN 2014: 4214-4222 - [c136]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen:
Short Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding. WSOM 2014: 65-74 - 2013
- [j61]Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse:
Feature selection for nonlinear models with extreme learning machines. Neurocomputing 102: 111-124 (2013) - [j60]Benoît Frénay, Gauthier Doquire, Michel Verleysen:
Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification. Neurocomputing 112: 64-78 (2013) - [j59]John Aldo Lee, Emilie Renard, Guillaume Bernard, Pierre Dupont, Michel Verleysen:
Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. Neurocomputing 112: 92-108 (2013) - [j58]Gauthier Doquire, Michel Verleysen:
A graph Laplacian based approach to semi-supervised feature selection for regression problems. Neurocomputing 121: 5-13 (2013) - [j57]Gauthier Doquire, Michel Verleysen:
Mutual information-based feature selection for multilabel classification. Neurocomputing 122: 148-155 (2013) - [j56]Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse:
Distance estimation in numerical data sets with missing values. Inf. Sci. 240: 115-128 (2013) - [j55]Benoît Frénay, Gauthier Doquire, Michel Verleysen:
Is mutual information adequate for feature selection in regression? Neural Networks 48: 1-7 (2013) - [c135]Gauthier Doquire, Benoît Frénay, Michel Verleysen:
Risk Estimation and Feature Selection. ESANN 2013 - [c134]Francisco J. García-Fernández, Michel Verleysen, John Aldo Lee, Ignacio Díaz Blanco:
Sensitivity to parameter and data variations in dimensionality reduction techniques. ESANN 2013 - [c133]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Segmentation with Incremental Classifiers. ICIAP (2) 2013: 81-90 - [c132]Michel Verleysen, John Aldo Lee:
Nonlinear Dimensionality Reduction for Visualization. ICONIP (1) 2013: 617-622 - [c131]Matthias Schäfer, Leishi Zhang, Tobias Schreck, Andrada Tatu, John Aldo Lee, Michel Verleysen, Daniel A. Keim:
Improving projection-based data analysis by feature space transformations. Visualization and Data Analysis 2013: 86540H - [c130]Francisco J. García-Fernández, Michel Verleysen, John A. Lee, Ignacio Díaz Blanco:
Stability Comparison of Dimensionality Reduction Techniques Attending to Data and Parameter Variations. VAMP@EuroVis 2013 - [c129]Emilie Renard, Pierre Dupont, Michel Verleysen:
User Control for Adjusting Conflicting Objectives in Parameter-dependent Visualization of Data. VAMP@EuroVis 2013 - 2012
- [j54]Gauthier Doquire, Michel Verleysen:
Feature selection with missing data using mutual information estimators. Neurocomputing 90: 3-11 (2012) - [j53]Gaël de Lannoy, Damien François, Jean Delbeke, Michel Verleysen:
Weighted Conditional Random Fields for Supervised Interpatient Heartbeat Classification. IEEE Trans. Biomed. Eng. 59(1): 241-247 (2012) - [c128]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental feature building and classification for image segmentation. ESANN 2012 - [c127]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
Cluster homogeneity as a semi-supervised principle for feature selection using mutual information. ESANN 2012 - [c126]Benoît Frénay, Gauthier Doquire, Michel Verleysen:
On the Potential Inadequacy of Mutual Information for Feature Selection. ESANN 2012 - [c125]Jérôme Paul, Michel Verleysen, Pierre Dupont:
The stability of feature selection and class prediction from ensemble tree classifiers. ESANN 2012 - [c124]Gauthier Doquire, Michel Verleysen:
Handling Imprecise Labels in Feature Selection with Graph Laplacian. ICPRAM (1) 2012: 162-169 - [c123]Gauthier Doquire, Michel Verleysen:
A Comparison of Multivariate Mutual Information Estimators for Feature Selection. ICPRAM (1) 2012: 176-185 - [i14]Daniel A. Keim, Fabrice Rossi, Thomas Seidl, Michel Verleysen, Stefan Wrobel:
Information Visualization, Visual Data Mining and Machine Learning (Dagstuhl Seminar 12081). Dagstuhl Reports 2(2): 58-83 (2012) - 2011
- [j52]Gauthier Doquire, Gaël de Lannoy, Damien François, Michel Verleysen:
Feature Selection for Interpatient Supervised Heart Beat Classification. Comput. Intell. Neurosci. 2011: 643816:1-643816:9 (2011) - [j51]Arnaud de Decker, Damien François, Michel Verleysen, John Aldo Lee:
Mode estimation in high-dimensional spaces with flat-top kernels: Application to image denoising. Neurocomputing 74(9): 1402-1410 (2011) - [j50]Benoît Frénay, Michel Verleysen:
Parameter-insensitive kernel in extreme learning for non-linear support vector regression. Neurocomputing 74(16): 2526-2531 (2011) - [c122]Gauthier Doquire, Gaël de Lannoy, Damien François, Michel Verleysen:
Feature Selection for Inter-patient Supervised Heart Beat Classification. BIOSIGNALS 2011: 67-73 - [c121]Gauthier Doquire, Michel Verleysen:
Feature Selection with Mutual Information for Uncertain Data. DaWaK 2011: 330-341 - [c120]Gauthier Doquire, Michel Verleysen:
Mutual information for feature selection with missing data. ESANN 2011 - [c119]Gauthier Doquire, Michel Verleysen:
Mutual information based feature selection for mixed data. ESANN 2011 - [c118]Gaël de Lannoy, Damien François, Michel Verleysen:
Class-Specific Feature Selection for One-Against-All Multiclass SVMs. ESANN 2011 - [c117]Gauthier Doquire, Michel Verleysen:
An Hybrid Approach to Feature Selection for Mixed Categorical and Continuous Data. KDIR 2011: 394-401 - [c116]Michel Verleysen:
Feature Selection for High-dimensional Data Analysis. IJCCI (NCTA) 2011: 23 - [c115]Gauthier Doquire, Michel Verleysen:
Feature Selection for Multi-label Classification Problems. IWANN (1) 2011: 9-16 - [c114]Gauthier Doquire, Michel Verleysen:
Graph Laplacian for Semi-supervised Feature Selection in Regression Problems. IWANN (1) 2011: 248-255 - [c113]Carlos Guerrero-Mosquera, Michel Verleysen, Ángel Navia-Vázquez:
Dimensionality reduction for EEG classification using Mutual Information and SVM. MLSP 2011: 1-6 - [c112]Benoît Frénay, Gaël de Lannoy, Michel Verleysen:
Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs. ECML/PKDD (1) 2011: 455-470 - [c111]Etienne Côme, Marie Cottrell, Michel Verleysen, Jérôme Lacaille:
Aircraft Engine Fleet Monitoring Using Self-Organizing Maps and Edit Distance. WSOM 2011: 298-307 - [c110]John Aldo Lee, Michel Verleysen:
Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants. ICCS 2011: 538-547 - [p1]Damien François, Vincent Wertz, Michel Verleysen:
Choosing the Metric: A Simple Model Approach. Meta-Learning in Computational Intelligence 2011: 97-115 - 2010
- [j49]Arnaud de Decker, John Aldo Lee, Michel Verleysen:
A principled approach to image denoising with similarity kernels involving patches. Neurocomputing 73(7-9): 1199-1209 (2010) - [j48]John Aldo Lee, Michel Verleysen:
Scale-independent quality criteria for dimensionality reduction. Pattern Recognit. Lett. 31(14): 2248-2257 (2010) - [c109]Gaël de Lannoy, Damien François, Jean Delbeke, Michel Verleysen:
Feature Relevance Assessment in Automatic Inter-patient Heart Beat Classification. BIOSIGNALS 2010: 13-20 - [c108]Gaël de Lannoy, Damien François, Jean Delbeke, Michel Verleysen:
Weighted SVMs and Feature Relevance Assessment in Supervised Heart Beat Classification. BIOSTEC (Selected Papers) 2010: 212-223 - [c107]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
Multi-Objective Semi-Supervised Feature Selection and Model Selection Based on Pearson's Correlation Coefficient. CIARP 2010: 509-516 - [c106]John A. Lee, Michel Verleysen:
On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding. COMPSTAT 2010: 337-346 - [c105]Etienne Côme, Marie Cottrell, Michel Verleysen, Jérôme Lacaille:
Self Organizing Star (SOS) for health monitoring. ESANN 2010 - [c104]Arnaud de Decker, John Aldo Lee, Damien François, Michel Verleysen:
Mode estimation in high-dimensional spaces with flat-top kernels: application to image denoising. ESANN 2010 - [c103]Benoît Frénay, Michel Verleysen:
Using SVMs with randomised feature spaces: an extreme learning approach. ESANN 2010 - [c102]