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ORCIDMichel Verleysen
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- affiliation: Université catholique de Louvain, Belgium
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2020 – today
- 2024
[j82]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
- [j81]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) - [j80]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
- [j79]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) - [j78]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
- [j77]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
- [j76]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) - [j75]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
- [j74]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) - [j73]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
- [j72]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
- [j71]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) - [j70]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
- [j69]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) - [j68]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
- [j67]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental classification of objects in scenes: Application to the delineation of images. Neurocomputing 152: 45-57 (2015) - [j66]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
- [j65]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) - [j64]Benoît Frénay, Michel Verleysen:
Pointwise probability reinforcements for robust statistical inference. Neural Networks 50: 124-141 (2014) - [j63]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
- [j62]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) - [j61]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) - [j60]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) - [j59]Gauthier Doquire, Michel Verleysen:
A graph Laplacian based approach to semi-supervised feature selection for regression problems. Neurocomputing 121: 5-13 (2013) - [j58]Gauthier Doquire, Michel Verleysen:
Mutual information-based feature selection for multilabel classification. Neurocomputing 122: 148-155 (2013) - [j57]Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse:
Distance estimation in numerical data sets with missing values. Inf. Sci. 240: 115-128 (2013) - [j56]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
- [j55]Gauthier Doquire, Michel Verleysen:
Feature selection with missing data using mutual information estimators. Neurocomputing 90: 3-11 (2012) - [j54]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
- [j53]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) - [j52]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) - [j51]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
- [j50]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) - [j49]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]Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen:
Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs. ESANN 2010 - [c101]Axel Wismüller, Michel Verleysen, Michaël Aupetit, John Aldo Lee:
Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning. ESANN 2010 - [c100]John Aldo Lee, Michel Verleysen:
Unsupervised dimensionality reduction: Overview and recent advances. IJCNN 2010: 1-8 - [c99]Victor Onclinx, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Dimensionality reduction by rank preservation. IJCNN 2010: 1-8 - [c98]Aurélien Hazan, Michel Verleysen, Marie Cottrell, Jérôme Lacaille:
Trajectory Clustering for Vibration Detection in Aircraft Engines. ICDM 2010: 362-375 - [c97]Etienne Côme, Marie Cottrell, Michel Verleysen, Jérôme Lacaille:
Aircraft Engine Health Monitoring Using Self-Organizing Maps. ICDM 2010: 405-417
2000 – 2009
- 2009
- [j48]John Aldo Lee, Michel Verleysen:
Quality assessment of dimensionality reduction: Rank-based criteria. Neurocomputing 72(7-9): 1431-1443 (2009) - [j47]Victor Onclinx, Vincent Wertz, Michel Verleysen:
Nonlinear data projection on non-Euclidean manifolds with controlled trade-off between trustworthiness and continuity. Neurocomputing 72(7-9): 1444-1454 (2009) - [j46]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K nearest neighbours with mutual information for simultaneous classification and missing data imputation. Neurocomputing 72(7-9): 1483-1493 (2009) - [j45]Vanessa Gómez-Verdejo, Michel Verleysen, Jérôme Fleury:
Information-theoretic feature selection for functional data classification. Neurocomputing 72(16-18): 3580-3589 (2009) - [j44]Elia Liitiäinen, Michel Verleysen, Francesco Corona, Amaury Lendasse:
Residual variance estimation in machine learning. Neurocomputing 72(16-18): 3692-3703 (2009) - [c96]Gaël de Lannoy, Michel Verleysen, Jean Delbeke:
Assessment and Comparison of Time Realignment Methods for Supervised Heart Beat Classification. BIOSIGNALS 2009: 239-244 - [c95]Michel Verleysen, Fabrice Rossi, Damien François:
Advances in Feature Selection with Mutual Information. Similarity-Based Clustering 2009: 52-69 - [c94]Arnaud de Decker, John Aldo Lee, Michel Verleysen:
Patch-based bilateral filter and local m-smoother for image denoising. ESANN 2009 - [c93]Benoît Frénay, Gaël de Lannoy, Michel Verleysen:
Improving the transition modelling in hidden Markov models for ECG segmentation. ESANN 2009 - [c92]Catherine Krier, Damien François, Fabrice Rossi, Michel Verleysen:
Supervised variable clustering for classification of NIR spectra. ESANN 2009 - [c91]John Aldo Lee, Arnaud de Decker, Michel Verleysen:
Adaptive anisotropic denoising: a bootstrapped procedure. ESANN 2009 - [c90]John Aldo Lee, Michel Verleysen:
Simbed: Similarity-Based Embedding. ICANN (2) 2009: 95-104 - [c89]Marie Cottrell, Patrice Gaubert, Cédric Eloy, Damien François, Geoffroy Hallaux, Jérôme Lacaille, Michel Verleysen:
Fault Prediction in Aircraft Engines Using Self-Organizing Maps. WSOM 2009: 37-44 - [e4]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
Similarity-Based Clustering, Recent Developments and Biomedical Applications [outcome of a Dagstuhl Seminar]. Lecture Notes in Computer Science 5400, Springer 2009, ISBN 978-3-642-01804-6 [contents] - [i13]Michel Verleysen, Fabrice Rossi, Damien François:
Advances in Feature Selection with Mutual Information. CoRR abs/0909.0635 (2009) - 2008
- [j43]Alex Assenza, Maurizio Valle, Michel Verleysen:
A Comparative Study of Various Probability Density Estimation Methods for Data Analysis. Int. J. Comput. Intell. Syst. 1(2): 188-201 (2008) - [j42]Cédric Archambeau, Nicolas Delannay, Michel Verleysen:
Mixtures of robust probabilistic principal component analyzers. Neurocomputing 71(7-9): 1274-1282 (2008) - [j41]Nicolas Delannay, Michel Verleysen:
Collaborative filtering with interlaced generalized linear models. Neurocomputing 71(7-9): 1300-1310 (2008) - [j40]John Aldo Lee, Frédéric Vrins, Michel Verleysen:
Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition. Neurocomputing 72(1-3): 47-56 (2008) - [j39]Dinh-Tuan Pham, Frédéric Vrins, Michel Verleysen:
On the Risk of Using RÉnyi's Entropy for Blind Source Separation. IEEE Trans. Signal Process. 56(10-1): 4611-4620 (2008) - [c88]Gaël de Lannoy, Arnaud de Decker, Michel Verleysen:
A Supervised Learning Approach Based on the Continuous Wavelet Transform for R Spike Detection in ECG. BIOSIGNALS (1) 2008: 140-145 - [c87]Gaël de Lannoy, Arnaud de Decker, Michel Verleysen:
A Supervised Wavelet Transform Algorithm for R Spike Detection in Noisy ECGs. BIOSTEC (Selected Papers) 2008: 256-264 - [c86]Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen:
Using the Delta Test for Variable Selection. ESANN 2008: 25-30 - [c85]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K-nearest neighbours based on mutual information for incomplete data classification. ESANN 2008: 37-42 - [c84]Victor Onclinx, Vincent Wertz, Michel Verleysen:
Nonlinear data projection on a sphere with controlled trade-off between trustworthiness and continuity. ESANN 2008: 43-48 - [c83]John Aldo Lee, Michel Verleysen:
Rank-based quality assessment of nonlinear dimensionality reduction. ESANN 2008: 49-54 - [c82]Rui Nian, Guangrong Ji, Michel Verleysen:
An Unsupervised Gaussian Mixture Classification Mechanism Based on Statistical Learning Analysis. FSKD (2) 2008: 14-18 - [c81]Rui Nian, Guangrong Ji, Michel Verleysen:
An Alternative to Center-Based Clustering Algorithm Via Statistical Learning Analysis. ICIC (2) 2008: 693-700 - [c80]Nicolas Delannay, Cédric Archambeau, Michel Verleysen:
Improving the Robustness to Outliers of Mixtures of Probabilistic PCAs. PAKDD 2008: 527-535 - [c79]John Aldo Lee, Michel Verleysen:
Quality assessment of nonlinear dimensionality reduction based on K-ary neighborhoods. FSDM 2008: 21-35 - [i12]Catherine Krier, Fabrice Rossi, Damien François, Michel Verleysen:
A data-driven functional projection approach for the selection of feature ranges in spectra with ICA or cluster analysis. CoRR abs/0802.0287 (2008) - 2007
- [j38]Geoffroy Simon, Michel Verleysen:
High-dimensional delay selection for regression models with mutual information and distance-to-diagonal criteria. Neurocomputing 70(7-9): 1265-1275 (2007) - [j37]Damien François, Fabrice Rossi, Vincent Wertz, Michel Verleysen:
Resampling methods for parameter-free and robust feature selection with mutual information. Neurocomputing 70(7-9): 1276-1288 (2007) - [j36]Amaury Lendasse, Erkki Oja, Olli Simula, Michel Verleysen:
Time series prediction competition: The CATS benchmark. Neurocomputing 70(13-15): 2325-2329 (2007) - [j35]Geoffroy Simon, John Aldo Lee, Marie Cottrell, Michel Verleysen:
Forecasting the CATS benchmark with the Double Vector Quantization method. Neurocomputing 70(13-15): 2400-2409 (2007) - [j34]Cédric Archambeau, Michel Verleysen:
Robust Bayesian clustering. Neural Networks 20(1): 129-138 (2007) - [j33]Frédéric Vrins, Dinh-Tuan Pham, Michel Verleysen:
Mixing and Non-Mixing Local Minima of the Entropy Contrast for Blind Source Separation. IEEE Trans. Inf. Theory 53(3): 1030-1042 (2007) - [j32]Damien François, Vincent Wertz, Michel Verleysen:
The Concentration of Fractional Distances. IEEE Trans. Knowl. Data Eng. 19(7): 873-886 (2007) - [j31]Frédéric Vrins, John Aldo Lee, Michel Verleysen:
A Minimum-Range Approach to Blind Extraction of Bounded Sources. IEEE Trans. Neural Networks 18(3): 809-822 (2007) - [j30]Sylvain Lespinats, Michel Verleysen, Alain Giron, Bernard Fertil:
DD-HDS: A Method for Visualization and Exploration of High-Dimensional Data. IEEE Trans. Neural Networks 18(5): 1265-1279 (2007) - [c78]Catherine Krier, Damien François, Fabrice Rossi, Michel Verleysen:
Feature clustering and mutual information for the selection of variables in spectral data. ESANN 2007: 157-162 - [c77]Cédric Archambeau, Nicolas Delannay, Michel Verleysen:
Mixtures of robust probabilistic principal component analyzers. ESANN 2007: 229-234 - [c76]Nicolas Delannay, Michel Verleysen:
Collaborative Filtering with interlaced Generalized Linear Models. ESANN 2007: 247-252 - [c75]Frédéric Vrins, Dinh-Tuan Pham, Michel Verleysen:
Is the General Form of Renyi's Entropy a Contrast for Source Separation? ICA 2007: 129-136 - [c74]Vanessa Gómez-Verdejo, Michel Verleysen, Jérôme Fleury:
Information-Theoretic Feature Selection for the Classification of Hysteresis Curves. IWANN 2007: 522-529 - [e3]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007. Dagstuhl Seminar Proceedings 07131, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2007 [contents] - [i11]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007 - [i10]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007 - [i9]Fabrice Rossi, Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Mutual information for the selection of relevant variables in spectrometric nonlinear modelling. CoRR abs/0709.3427 (2007) - [i8]Fabrice Rossi, Damien François, Vincent Wertz, Marc Meurens, Michel Verleysen:
Fast Selection of Spectral Variables with B-Spline Compression. CoRR abs/0709.3639 (2007) - [i7]Damien François, Fabrice Rossi, Vincent Wertz, Michel Verleysen:
Resampling methods for parameter-free and robust feature selection with mutual information. CoRR abs/0709.3640 (2007) - [i6]Fabrice Rossi, Nicolas Delannay, Brieuc Conan-Guez, Michel Verleysen:
Representation of Functional Data in Neural Networks. CoRR abs/0709.3641 (2007) - [i5]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps. CoRR abs/cs/0701052 (2007) - [i4]Eric de Bodt, Marie Cottrell, Patrick Letrémy, Michel Verleysen:
On the use of self-organizing maps to accelerate vector quantization. CoRR abs/math/0701142 (2007) - [i3]Eric de Bodt, Marie Cottrell, Michel Verleysen:
Statistical tools to assess the reliability of self-organizing maps. CoRR abs/math/0701144 (2007) - 2006
- [j29]Marie Cottrell, Michel Verleysen:
Advances in Self-Organizing Maps. Neural Networks 19(6-7): 721-722 (2006) - [j28]Geoffroy Simon, John Aldo Lee, Michel Verleysen:
Unfolding preprocessing for meaningful time series clustering. Neural Networks 19(6-7): 877-888 (2006) - [c73]Amaury Lendasse, Francesco Corona, Jin Hao, Nima Reyhani, Michel Verleysen:
Determination of the Mahalanobis matrix using nonparametric noise estimations. ESANN 2006: 227-232 - [c72]Damien François, Vincent Wertz, Michel Verleysen:
The permutation test for feature selection by mutual information. ESANN 2006: 239-244 - [c71]John Aldo Lee, Frédéric Vrins, Michel Verleysen:
Non-orthogonal Support Width ICA. ESANN 2006: 351-358 - [c70]Geoffroy Simon, Michel Verleysen:
Lag selection for regression models using high-dimensional mutual information. ESANN 2006: 395-400 - [c69]Frédéric Vrins, Michel Verleysen:
Minimum Support ICA Using Order Statistics. Part I: Quasi-range Based Support Estimation. ICA 2006: 262-269 - [c68]Frédéric Vrins, Michel Verleysen:
Minimum Support ICA Using Order Statistics. Part II: Performance Analysis. ICA 2006: 270-277 - [c67]Frédéric Vrins, Deniz Erdogmus, Christian Jutten, Michel Verleysen:
Zero-Entropy Minimization for Blind Extraction of Bounded Sources (BEBS). ICA 2006: 747-754 - [c66]Fabrice Rossi, Damien François, Vincent Wertz, Michel Verleysen:
A Functional Approach to Variable Selection in Spectrometric Problems. ICANN (1) 2006: 11-20 - [c65]Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Michel Verleysen, Alberto Guillén:
Effective Input Variable Selection for Function Approximation. ICANN (1) 2006: 41-50 - [c64]Cédric Archambeau, Nicolas Delannay, Michel Verleysen:
Robust probabilistic projections. ICML 2006: 33-40 - [c63]Nicolas Delannay, Cédric Archambeau, Michel Verleysen:
Automatic Adjustment of Discriminant Adaptive Nearest Neighbor. ICPR (2) 2006: 552-535 - [c62]Cédric Archambeau, Maurizio Valle, Alex Assenza, Michel Verleysen:
Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures. ISCAS 2006 - [i2]Marie Cottrell, Michel Verleysen:
Advances in Self Organising Maps. CoRR abs/cs/0611058 (2006) - [i1]Frédéric Vrins, Dinh-Tuan Pham, Michel Verleysen:
Mixing and non-mixing local minima of the entropy contrast for blind source separation. CoRR abs/cs/0611106 (2006) - 2005
- [j27]Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Vector quantization: a weighted version for time-series forecasting. Future Gener. Comput. Syst. 21(7): 1056-1067 (2005) - [j26]Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen:
Fast bootstrap methodology for regression model selection. Neurocomputing 64: 161-181 (2005) - [j25]Fabrice Rossi, Nicolas Delannay, Brieuc Conan-Guez, Michel Verleysen:
Representation of functional data in neural networks. Neurocomputing 64: 183-210 (2005) - [j24]John Aldo Lee, Michel Verleysen:
Nonlinear dimensionality reduction of data manifolds with essential loops. Neurocomputing 67: 29-53 (2005) - [j23]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Time series forecasting: Obtaining long term trends with self-organizing maps. Pattern Recognit. Lett. 26(12): 1795-1808 (2005) - [j22]Frédéric Vrins, Michel Verleysen:
On the entropy minimization of a linear mixture of variables for source separation. Signal Process. 85(5): 1029-1044 (2005) - [j21]Frédéric Vrins, Michel Verleysen:
Information theoretic versus cumulant-based contrasts for multimodal source separation. IEEE Signal Process. Lett. 12(3): 190-193 (2005) - [c61]Luh Yen, Denis Vanvyve, Fabien Wouters, François Fouss, Michel Verleysen, Marco Saerens:
clustering using a random walk based distance measure. ESANN 2005: 317-324 - [c60]Damien François, Vincent Wertz, Michel Verleysen:
Non-Euclidean metrics for similarity search in noisy datasets. ESANN 2005: 339-344 - [c59]Antti Sorjamaa, Amaury Lendasse, Michel Verleysen:
Pruned lazy learning models for time series prediction. ESANN 2005: 509-514 - [c58]John Aldo Lee, Frédéric Vrins, Michel Verleysen:
A simple ICA algorithm for non-differentiable contrasts. EUSIPCO 2005: 1-4 - [c57]Frédéric Vrins, John Aldo Lee, Michel Verleysen:
Can we always trust entropy minima in the ICA context? EUSIPCO 2005: 1-4 - [c56]Cédric Archambeau, Michel Verleysen:
Manifold Constrained Variational Mixtures. ICANN (2) 2005: 279-284 - [c55]Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel Verleysen:
LS-SVM Hyperparameter Selection with a Nonparametric Noise Estimator. ICANN (2) 2005: 625-630 - [c54]Frédéric Vrins, Michel Verleysen, Christian Jutten:
SWM: a class of convex contrasts for source separation. ICASSP (5) 2005: 161-164 - [c53]Dinh-Tuan Pham, Frédéric Vrins, Michel Verleysen:
Spurious entropy minima for multimodal source separation. ISSPA 2005: 37-40 - [c52]Michel Verleysen, Damien François:
The Curse of Dimensionality in Data Mining and Time Series Prediction. IWANN 2005: 758-770 - [c51]Cédric Archambeau, Michel Verleysen:
Manifold Constrained Finite Gaussian Mixtures. IWANN 2005: 820-828 - [c50]Frédéric Vrins, John Aldo Lee, Michel Verleysen:
Filtering-Free Blind Separation of Correlated Images. IWANN 2005: 1091-1099 - 2004
- [j20]Cédric Archambeau, Jean Delbeke, Claude Veraart, Michel Verleysen:
Prediction of visual perceptions with artificial neural networks in a visual prosthesis for the blind. Artif. Intell. Medicine 32(3): 183-194 (2004) - [j19]Eric de Bodt, Marie Cottrell, Patrick Letrémy, Michel Verleysen:
On the use of self-organizing maps to accelerate vector quantization. Neurocomputing 56: 187-203 (2004) - [j18]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis. Neurocomputing 57: 49-76 (2004) - [j17]Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen:
Double quantization of the regressor space for long-term time series prediction: method and proof of stability. Neural Networks 17(8-9): 1169-1181 (2004) - [c49]Cédric Archambeau, Frédéric Vrins, Michel Verleysen:
Flexible and Robust Bayesian Classification by Finite Mixture Models. ESANN 2004: 75-80 - [c48]Frédéric Vrins, Cédric Archambeau, Michel Verleysen:
Towards a Local Separation Performances Estimator Using Common ICA Contrast Functions? ESANN 2004: 211-216 - [c47]John Aldo Lee, Michel Verleysen:
How to project 'circular' manifolds using geodesic distances? ESANN 2004: 223-230 - [c46]Nicolas Delannay, Fabrice Rossi, Brieuc Conan-Guez, Michel Verleysen:
Functional radial basis function networks. ESANN 2004: 313-318 - [c45]Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen:
Fast bootstrap for least-square support vector machines. ESANN 2004: 525-530 - [c44]John Aldo Lee, Christian Jutten, Michel Verleysen:
Non-linear ICA by Using Isometric Dimensionality Reduction. ICA 2004: 710-717 - [c43]Frédéric Vrins, Christian Jutten, Michel Verleysen:
Sensor Array and Electrode Selection for Non-invasive Fetal Electrocardiogram Extraction by Independent Component Analysis. ICA 2004: 1017-1014 - [c42]Cédric Archambeau, Torsten Butz, Vlad Popovici, Michel Verleysen, Jean-Philippe Thiran:
Supervised Nonparametric Information Theoretic Classification. ICPR (3) 2004: 414-417 - 2003
- [b1]Carlos Dualibe, Michel Verleysen, Paul G. A. Jespers:
Design of analog fuzzy logic controllers in CMOS technologies - implementation, test and application. Kluwer 2003, pp. I-VIII, 1-214 - [j16]Nabil Benoudjit, Michel Verleysen:
On the Kernel Widths in Radial-Basis Function Networks. Neural Process. Lett. 18(2): 139-154 (2003) - [c41]Cédric Archambeau, John Aldo Lee, Michel Verleysen:
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures. ESANN 2003: 99-106 - [c40]Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Fast approximation of the bootstrap for model selection. ESANN 2003: 475-480 - [c39]John Aldo Lee, Cédric Archambeau, Michel Verleysen:
Locally Linear Embedding versus Isotop. ESANN 2003: 527-534 - [c38]Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Model Selection with Cross-Validations and Bootstraps - Application to Time Series Prediction with RBFN Models. ICANN 2003: 573-580 - [c37]Amaury Lendasse, Damien François, Vincent Wertz, Michel Verleysen:
Nonlinear Time Series Prediction by Weighted Vector Quantization. International Conference on Computational Science 2003: 417-426 - [c36]Michel Verleysen, Damien François, Geoffroy Simon, Vincent Wertz:
On the Effects of Dimensionality on Data Analysis with Neural Networks. IWANN (2) 2003: 105-112 - [c35]Geoffroy Simon, Amaury Lendasse, Michel Verleysen:
Bootstrap for Model Selection: Linear Approximation of the Optimism. IWANN (1) 2003: 182-189 - [c34]Frédéric Vrins, John Aldo Lee, Michel Verleysen, Vincent Vigneron, Christian Jutten:
Improving independent component analysis performances by variable selection. NNSP 2003: 359-368 - 2002
- [j15]Michel Verleysen, Joos Vandewalle:
Special issue on fundamental and information processing aspects of neurocomputing. Neurocomputing 48(1-4): 1-2 (2002) - [j14]Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Forecasting electricity consumption using nonlinear projection and self-organizing maps. Neurocomputing 48(1-4): 299-311 (2002) - [j13]Eric de Bodt, Marie Cottrell, Michel Verleysen:
Statistical tools to assess the reliability of self-organizing maps. Neural Networks 15(8-9): 967-978 (2002) - [j12]John Aldo Lee, Michel Verleysen:
Self-organizing maps with recursive neighborhood adaptation. Neural Networks 15(8-9): 993-1003 (2002) - [j11]Jader A. De Lima, Sidnei F. Silva, Adriano S. Cordeiro, Michel Verleysen:
A CMOS/SOI Single-input PWM Discriminator for Low-voltage Body-implanted Applications. VLSI Design 15(1): 469-476 (2002) - [c33]Amaury Lendasse, Marie Cottrell, Vincent Wertz, Michel Verleysen:
Prediction of electric load using Kohonen maps - Application to the Polish electricity consumption. ACC 2002: 3684-3689 - [c32]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Curvilinear Distance Analysis versus Isomap. ESANN 2002: 185-192 - [c31]Nabil Benoudjit, Cédric Archambeau, Amaury Lendasse, John Aldo Lee, Michel Verleysen:
Width optimization of the Gaussian kernels in Radial Basis Function Networks. ESANN 2002: 425-432 - [c30]John Aldo Lee, Michel Verleysen:
Nonlinear Projection with the Isotop Method. ICANN 2002: 933-938 - [e2]Michel Verleysen:
10th Eurorean Symposium on Artificial Neural Networks, ESANN 2002, Bruges, Belgium, April 24-26, 2002, Proceedings. 2002, ISBN 2-930307-02-1 [contents] - 2001
- [c29]Eric de Bodt, Marie Cottrell, Michel Verleysen:
Are they really neighbors? A statistical analysis of the SOM algorithm output. AISTATS 2001: 87-92 - [c28]Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen:
Input data reduction for the prediction of financial time series. ESANN 2001: 237-244 - [c27]Carlos Dualibe, Paul G. A. Jespers, Michel Verleysen:
Embedded fuzzy control for automatic channel equalization after digital transmissions. ISCAS (3) 2001: 173-176 - [c26]Carlos Dualibe, Paul G. A. Jespers, Michel Verleysen:
On Designing Mixed-Signal Fuzzy Logic Controllers as Embedded Subsystems in Standard CMOS Technologies. SBCCI 2001: 194-200 - [c25]Marie Cottrell, Eric de Bodt, Michel Verleysen:
A Statistical Tool to Assess the Reliability of Self-Organizing Maps. WSOM 2001: 7-14 - [c24]John A. Lee, Nicolas Donckers, Michel Verleysen:
Recursive learning rules for SOMs. WSOM 2001: 67-72 - 2000
- [c23]John Aldo Lee, Amaury Lendasse, Nicolas Donckers, Michel Verleysen:
A robust non-linear projection method. ESANN 2000: 13-20 - [c22]Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Time series forecasting using CCA and Kohonen maps - application to electricity consumption. ESANN 2000: 329-334 - [c21]Jader A. De Lima, Sidnei F. Silva, Adriano S. Cordeiro, Alexandro C. Araujo, Michel Verleysen:
A low-power silicon-on-insulator PWM discriminator for biomedical applications. ISCAS 2000: 277-280 - [c20]Carlos Dualibe, Paul G. A. Jespers, Michel Verleysen:
A 5.26 Mflips programmable analogue fuzzy logic controller in a standard CMOS 2.4 μ technology. ISCAS 2000: 377-380 - [c19]Nicolas Donckers, Carlos Dualibe, Michel Verleysen:
A current-mode CMOS loser-take-all with minimum function for neural computations. ISCAS 2000: 415-418
1990 – 1999
- 1999
- [c18]Eric de Bodt, Marie Cottrell, Michel Verleysen:
Using the Kohonen algorithm for quick initialization of Simple Competitive Learning algorithm. ESANN 1999: 19-26 - [c17]Nicolas Donckers, Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Extraction of intrinsic dimension using CCA - Application to blind sources separation. ESANN 1999: 339-344 - [c16]Michel Verleysen, Eric de Bodt, Amaury Lendasse:
Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection. IWANN (2) 1999: 596-605 - 1998
- [j10]C. Amerijckx, Michel Verleysen, Philippe Thissen, Jean-Didier Legat:
Image compression by self-organized Kohonen map. IEEE Trans. Neural Networks 9(3): 503-507 (1998) - [c15]Amaury Lendasse, Michel Verleysen, Eric de Bodt, Marie Cottrell, Philippe Grégoire:
Forecasting time-series by Kohonen classification. ESANN 1998: 221-226 - 1997
- [j9]Katerina Hlavácková, Michel Verleysen:
Placing spline knots in neural networks using splines as activation functions. Neurocomputing 17(3-4): 159-166 (1997) - [c14]Eric de Bodt, Michel Verleysen, Marie Cottrell:
Kohonen maps versus vector quantization for data analysis. ESANN 1997 - [e1]Michel Verleysen:
5th Eurorean Symposium on Artificial Neural Networks, ESANN 1997, Bruges, Belgium, April 16-18, 1997, Proceedings. D-Facto public 1997, ISBN 2-9600049-7-3 [contents] - 1995
- [j8]François Blayo, Michel Verleysen:
Editorial. Neural Process. Lett. 2(3): 1 (1995) - [c13]Jean-Luc Voz, Michel Verleysen, Philippe Thissen, Jean-Didier Legat:
Suboptimal Bayesian classification by vector quantization with small clusters. ESANN 1995 - [c12]Michel Verleysen, Jean-Luc Voz, Philippe Thissen, Jean-Didier Legat:
A statistical neural network for high-dimensional vector classification. ICNN 1995: 990-994 - [c11]Jean-Luc Voz, Michel Verleysen, Philippe Thissen, Jean-Didier Legat:
A Practical View of Suboptimal Bayesian Classification with Radial Gaussian Kernels. IWANN 1995: 404-411 - [c10]Philippe Thissen, Michel Verleysen, Jean-Didier Legat, Jordi Madrenas, Jordi Domínguez:
A VLSI System for Neural Bayesian and LVQ Classification. IWANN 1995: 696-703 - [c9]Philippe Thissen, Michel Verleysen, Jean-Didier Legat:
An Associative Processor Dedicated to Classification by Neural Methods. IWANN 1995: 704-711 - 1994
- [j7]Michel Verleysen, Philippe Thissen, Jean-Luc Voz, Jordi Madrenas:
An analog processor architecture for a neural network classifier. IEEE Micro 14(3): 16-28 (1994) - [j6]François Blayo, Michel Verleysen:
Editorial. Neural Process. Lett. 1(1): 1 (1994) - [c8]Pierre Comon, Jean-Luc Voz, Michel Verleysen:
Estimation of performance bounds in supervised classification. ESANN 1994 - [c7]Michel Verleysen, Katerina Hlavácková:
An optimized RBF network for approximation of functions. ESANN 1994 - 1993
- [j5]Damien Macq, Michel Verleysen, Paul G. A. Jespers, Jean-Didier Legat:
Analog implementation of a Kohonen map with on-chip learning. IEEE Trans. Neural Networks 4(3): 456-461 (1993) - [c6]Benoît Simon, Benoît Macq, Michel Verleysen:
Laplacian pyramid with multilayer perceptrons interpolators. ESANN 1993 - [c5]Michel Verleysen, Philippe Thissen, Jean-Didier Legat:
Optimal decision surfaces in LVQ1 classiffication of patterns. ESANN 1993 - [c4]Michel Verleysen, Philippe Thissen, Jean-Didier Legat:
Linear Vector Classification: An Improvement on LVQ Algorithms to Create Classes of Patterns. IWANN 1993: 340-345 - 1992
- [c3]Jean-Didier Legat, J. P. Cornil, Damien Macq, Michel Verleysen:
A real-time VLSI-based architecture for multi-motion estimation. ICPR (4) 1992: 147-150 - 1991
- [c2]Michel Verleysen, Paul G. A. Jespers:
Analog VLSI Synapse Matrix with Enhanced Stochastic Computations. IWANN 1991: 315-321
1980 – 1989
- 1989
- [j4]Michel Verleysen, Bruno Sirletti, Andre M. Vandemeulebroecke, Paul G. A. Jespers:
Neural networks for high-storage content-addressable memory: VLSI circuit and learning algorithm. IEEE J. Solid State Circuits 24(3): 562-569 (1989) - [j3]Michel Verleysen, Paul G. A. Jespers:
An analog VLSI implementation of Hopfield's neural network. IEEE Micro 9(6): 46-55 (1989) - [c1]Michel Verleysen, Paul G. A. Jespers:
An Analog VLSI Architecture for Large Neural Networks. NATO Neurocomputing 1989: 141-144 - 1988
- [j2]Bruno Sirletti, Michel Verleysen, Andre M. Vandemeulebroecke, Paul G. A. Jespers:
An algorithm for pattern recognition with VLSI neural networks. Neural Networks 1(Supplement-1): 53 (1988) - [j1]Michel Verleysen, Bruno Sirletti, Paul G. A. Jespers:
A large VLSI Hopfield network for pattern recognition problems. Neural Networks 1(Supplement-1): 414-418 (1988)
Coauthor Index
John A. Lee 0001
aka: John Aldo Lee
aka: John Aldo Lee
[j82] [j80] [c176] [j79] [j78] [i17] [c175] [c174] [c173] [i16] [j73] [c169] [c167] [c163] [c162] [j71] [c150] [j67] [j66] [c147] [c145] [c144] [c141] [c140] [c138] [c136] [j60] [c134] [c133] [c132] [c131] [c130] [c128] [j52] [c110] [j50] [j49] [c106] [c104] [c101] [c100] [c99] [j48] [c94] [c91] [c90] [j40] [c83] [c79] [j35] [j31] [j28] [c71] [j24] [c58] [c57] [c50] [j18] [c47] [c44] [c41] [c39] [c34] [j14] [j12] [c32] [c31] [c30] [c28] [c24] [c23] [c22]
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