John A. Lee

According to our database, John A. Lee authored at least 109 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Investigating latent representations and generalization in deep neural networks for tabular data.

Edouard Couplet, Pierre Lambert, Michel Verleysen, John A. Lee, Cyril de Bodt

Neurocomputing, 2024

The proton arc therapy treatment planning problem is NP-Hard.

Viktor Wase, Sophie Wuyckens, John A. Lee, Michael Saint-Guillain

Comput. Biol. Medicine, 2024

2023

Semi-supervised <i>t</i>-SNE with multi-scale neighborhood preservation.

Walter Serna-Serna, Cyril de Bodt, Andrés Marino Álvarez-Meza, John A. Lee, Michel Verleysen, Álvaro Ángel Orozco-Guitiérrez

Neurocomputing, 2023

Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? - Application to proton therapy dose prediction for head and neck cancer patients.

Margerie Huet-Dastarac, Dan Nguyen, Steve B. Jiang, John A. Lee, Ana M. Barragan-Montero

CoRR, 2023

Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration.

Pierre Lambert, John A. Lee, Edouard Couplet, Cyril de Bodt

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

On the number of latent representations in deep neural networks for tabular data.

Edouard Couplet, Pierre Lambert, Michel Verleysen, John A. Lee, Cyril de Bodt

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer.

Ana Maria Barragán-Montero, Robin Tilman, Margerie Huet-Dastarac, John A. Lee

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2022

Fast Multiscale Neighbor Embedding.

Cyril de Bodt, Dounia Mulders, Michel Verleysen, John Aldo Lee

IEEE Trans. Neural Networks Learn. Syst., 2022

Compressive Imaging Through Optical Fiber with Partial Speckle Scanning.

Stéphanie Guérit, Siddharth Sivankutty, John A. Lee, Hervé Rigneault, Laurent Jacques

SIAM J. Imaging Sci., 2022

SQuadMDS: A lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like <i>t</i>-SNE and UMAP.

Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee

Neurocomputing, 2022

Deep learning to detect bacterial colonies for the production of vaccines.

Thomas Beznik, Paul Smyth, Gaël de Lannoy, John A. Lee

Neurocomputing, 2022

SQuadMDS: a lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP.

Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee

CoRR, 2022

Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers.

Sophie Wuyckens, Michael Saint-Guillain, Guillaume Janssens, Lewei Zhao, Xiaoqiang Li, Xuanfeng Ding, Edmond Sterpin, John A. Lee, Kevin Souris

Comput. Biol. Medicine, 2022

Tuning Database-Friendly Random Projection Matrices for Improved Distance Preservation on Specific Data.

Daniel López Sánchez, Cyril de Bodt, John A. Lee, Angélica González Arrieta, Juan M. Corchado

Appl. Intell., 2022

2021

Compressive lensless endoscopy with partial speckle scanning.

Stéphanie Guérit, Siddharth Sivankutty, John Aldo Lee, Hervé Rigneault, Laurent Jacques

CoRR, 2021

Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT.

Eliott Brion, Jean Léger, Ana M. Barragan-Montero, Nicolas Meert, John A. Lee, Benoît Macq

Comput. Biol. Medicine, 2021

Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models.

John A. Lee, Alyssa Vanginderdeuren, Margerie Huet-Dastarac, Ana Maria Barragán-Montero

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding.

Pierre Lambert, John A. Lee, Michel Verleysen, Cyril de Bodt

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

Stochastic quartet approach for fast multidimensional scaling.

Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Perplexity-free Parametric t-SNE.

Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Nonlinear Dimensionality Reduction With Missing Data Using Parametric Multiple Imputations.

Cyril de Bodt, Dounia Mulders, Michel Verleysen, John Aldo Lee

IEEE Trans. Neural Networks Learn. Syst., 2019

Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation.

Umair Javaid, Damien Dasnoy, John A. Lee

Proceedings of the Medical Imaging 2019: Image Processing, 2019

Using planning CTs to enhance CNN-based bladder segmentation on cone beam CT.

Eliott Brion, Jean Léger, Umair Javaid, John A. Lee, Christophe De Vleeschouwer, Benoît Macq

Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019

Tensor factorization to extract patterns in multimodal EEG data.

Dounia Mulders, Cyril de Bodt, Nicolas Lejeune, John A. Lee, André Mouraux, Michel Verleysen

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Class-aware t-SNE: cat-SNE.

Cyril de Bodt, Dounia Mulders, Daniel López Sánchez, Michel Verleysen, John A. Lee

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018

A novel method for network intrusion detection based on nonlinear SNE and SVM.

Yasir Hamid, Ludovic Journaux, John A. Lee, M. Sugumaran

Int. J. Artif. Intell. Soft Comput., 2018

Compressive Sampling Approach for Image Acquisition with Lensless Endoscope.

Stéphanie Guérit, Siddharth Sivankutty, Camille Scotté, John Aldo Lee, Hervé Rigneault, Laurent Jacques

CoRR, 2018

Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks.

Umair Javaid, John A. Lee

CoRR, 2018

Capturing variabilities from Computed Tomography images with Generative Adversarial Networks (GANs).

Umair Javaid, John A. Lee

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Information visualisation and machine learning: latest trends towards convergence.

Benoît Frénay, Bruno Dumas, John A. Lee

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Extensive assessment of Barnes-Hut t-SNE.

Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Perplexity-free t-SNE and twice Student tt-SNE.

Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Contour Propagation in CT Scans with Convolutional Neural Networks.

Jean Léger, Eliott Brion, Umair Javaid, John A. Lee, Christophe De Vleeschouwer, Benoît Macq

Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2018

Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet.

Umair Javaid, Damien Dasnoy, John A. Lee

Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2018

2017

Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis.

Dominik Sacha, Leishi Zhang, Michael Sedlmair, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, Daniel A. Keim

IEEE Trans. Vis. Comput. Graph., 2017

What you see is what you can change: Human-centered machine learning by interactive visualization.

Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, Daniel A. Keim

Neurocomputing, 2017

Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity.

Andrés Marino Álvarez-Meza, John Aldo Lee, Michel Verleysen, Germán Castellanos-Domínguez

Neurocomputing, 2017

Comparing dynamics of fluency and inter-limb coordination in climbing activities using multi-scale Jensen-Shannon embedding and clustering.

Romain Hérault, Dominic Orth, Ludovic Seifert, Jérémie Boulanger, John Aldo Lee

Data Min. Knowl. Discov., 2017

Large-scale nonlinear dimensionality reduction for network intrusion detection.

Yasir Hamid, Ludovic Journaux, John Aldo Lee, Lucile Sautot, Nabi Bushra, M. Sugumaran

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016

Blind Deconvolution of PET Images using Anatomical Priors.

Stéphanie Guérit, Adriana Gonzalez, Anne Bol, John A. Lee, Laurent Jacques

CoRR, 2016

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16).

Vinayak Abrol, Olivier Absil, Pierre-Antoine Absil, Sandrine Anthoine, Philippe Antoine, Thomas Arildsen, Nancy Bertin, Folkert Bleichrodt, Jérôme Bobin, Anne Bol, Antoine Bonnefoy, Francesco Caltagirone, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang

CoRR, 2016

Multi-step-ahead forecasting using kernel adaptive filtering.

Sergio García-Vega, Germán Castellanos-Domínguez, Michel Verleysen, John Aldo Lee

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Image deconvolution by local order preservation of pixels values.

Stéphanie Guérit, Laurent Jacques, John A. Lee

Proceedings of the 24th European Signal Processing Conference, 2016

Human-centered machine learning through interactive visualization: review and open challenges.

Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Daniel Weiskopf, Stephen C. North, Daniel A. Keim

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure.

John Aldo Lee, Diego Hernán Peluffo-Ordóñez, Michel Verleysen

Neurocomputing, 2015

Incremental classification of objects in scenes: Application to the delineation of images.

Guillaume Bernard, Michel Verleysen, John Aldo Lee

Neurocomputing, 2015

Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding.

Romain Hérault, Jérémie Boulanger, Ludovic Seifert, John Aldo Lee

Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), 2015

Post-reconstruction deconvolution of PET images by total generalized variation regularization.

Stéphanie Guérit, Laurent Jacques, Benoît Macq, John A. Lee

Proceedings of the 23rd European Signal Processing Conference, 2015

Geometrical homotopy for data visualization.

Diego Hernán Peluffo-Ordóñez, Juan Carlos Alvarado-Pérez, John Aldo Lee, Michel Verleysen

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Unsupervised dimensionality reduction: the challenge of big data visualization.

Kerstin Bunte, John Aldo Lee

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013).

Mark J. Embrechts, Fabrice Rossi, Frank-Michael Schleif, John Aldo Lee

Neurocomputing, 2014

Short Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding.

Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen

Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Unsupervised Relevance Analysis for Feature Extraction and Selection - A Distance-based Approach for Feature Relevance.

Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen, José L. Rodríguez, Germán Castellanos-Domínguez

Proceedings of the ICPRAM 2014, 2014

Recent methods for dimensionality reduction: A brief comparative analysis.

Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction.

John Aldo Lee, Diego Hernán Peluffo-Ordóñez, Michel Verleysen

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Generalized kernel framework for unsupervised spectral methods of dimensionality reduction.

Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen

Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Two key properties of dimensionality reduction methods.

John Aldo Lee, Michel Verleysen

Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013

Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation.

John Aldo Lee, Emilie Renard, Guillaume Bernard, Pierre Dupont, Michel Verleysen

Neurocomputing, 2013

Stability Comparison of Dimensionality Reduction Techniques Attending to Data and Parameter Variations.

Francisco J. García-Fernández, Michel Verleysen, John A. Lee, Ignacio Díaz Blanco

Proceedings of the 1st International Workshop on Visual Analytics Using Multidimensional Projections, 2013

Improving projection-based data analysis by feature space transformations.

Matthias Schäfer, Leishi Zhang, Tobias Schreck, Andrada Tatu, John Aldo Lee, Michel Verleysen, Daniel A. Keim

Proceedings of the Visualization and Data Analysis 2013, 2013

Nonlinear Dimensionality Reduction for Visualization.

Michel Verleysen, John Aldo Lee

Proceedings of the Neural Information Processing - 20th International Conference, 2013

Segmentation with Incremental Classifiers.

Guillaume Bernard, Michel Verleysen, John Aldo Lee

Proceedings of the Image Analysis and Processing - ICIAP 2013, 2013

Sensitivity to parameter and data variations in dimensionality reduction techniques.

Francisco J. García-Fernández, Michel Verleysen, John Aldo Lee, Ignacio Díaz Blanco

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012

Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy.

Tony Shepherd, Mika Teräs, Reinhard Beichel, Ronald Boellaard, Michel Bruynooghe, Volker Dicken, Mark J. Gooding, Peter J. Julyan, John Aldo Lee, Sébastien Lefèvre, Michael Mix, Valery Naranjo, Xiaodong Wu, Habib Zaidi, Ziming Zeng, Heikki Minn

IEEE Trans. Medical Imaging, 2012

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011).

John Aldo Lee, Petra Schneider, John A. Quinn

Neurocomputing, 2012

Type 1 and 2 symmetric divergences for stochastic neighbor embedding.

John Aldo Lee

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Incremental feature building and classification for image segmentation.

Guillaume Bernard, Michel Verleysen, John Aldo Lee

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants.

John Aldo Lee, Michel Verleysen

Proceedings of the International Conference on Computational Science, 2011

Advances in artificial neural networks, machine learning, and computational intelligence.

John Aldo Lee, Frank-Michael Schleif, Thomas Martinetz

Neurocomputing, 2011

Mode estimation in high-dimensional spaces with flat-top kernels: Application to image denoising.

Arnaud de Decker, Damien François, Michel Verleysen, John Aldo Lee

Neurocomputing, 2011

2010

Scale-independent quality criteria for dimensionality reduction.

John Aldo Lee, Michel Verleysen

Pattern Recognit. Lett., 2010

A principled approach to image denoising with similarity kernels involving patches.

Arnaud de Decker, John Aldo Lee, Michel Verleysen

Neurocomputing, 2010

Advances in computational intelligence and learning (ESANN 2009).

Cecilio Angulo, John Aldo Lee, Frank-Michael Schleif

Neurocomputing, 2010

Dimensionality reduction by rank preservation.

Victor Onclinx, John Aldo Lee, Vincent Wertz, Michel Verleysen

Proceedings of the International Joint Conference on Neural Networks, 2010

Unsupervised dimensionality reduction: Overview and recent advances.

John Aldo Lee, Michel Verleysen

Proceedings of the International Joint Conference on Neural Networks, 2010

Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning.

Axel Wismüller, Michel Verleysen, Michaël Aupetit, John Aldo Lee

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding.

John A. Lee, Michel Verleysen

Proceedings of the 19th International Conference on Computational Statistics, 2010

2009

Quality assessment of dimensionality reduction: Rank-based criteria.

John Aldo Lee, Michel Verleysen

Neurocomputing, 2009

Simbed: Similarity-Based Embedding.

John Aldo Lee, Michel Verleysen

Proceedings of the Artificial Neural Networks, 2009

Adaptive anisotropic denoising: a bootstrapped procedure.

John Aldo Lee, Arnaud de Decker, Michel Verleysen

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Patch-based bilateral filter and local m-smoother for image denoising.

Arnaud de Decker, John Aldo Lee, Michel Verleysen

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008

Edge-Preserving Filtering of Images with Low Photon Counts.

John Aldo Lee, Xavier Geets, Vincent Grégoire, Anne Bol

IEEE Trans. Pattern Anal. Mach. Intell., 2008

Quality assessment of nonlinear dimensionality reduction based on K-ary neighborhoods.

John Aldo Lee, Michel Verleysen

Proceedings of the Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery, 2008

Blind source separation based on endpoint estimation with application to the MLSP 2006 data competition.

John Aldo Lee, Frédéric Vrins, Michel Verleysen

Neurocomputing, 2008

Rank-based quality assessment of nonlinear dimensionality reduction.

John Aldo Lee, Michel Verleysen

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

A Minimum-Range Approach to Blind Extraction of Bounded Sources.

Frédéric Vrins, John Aldo Lee, Michel Verleysen

IEEE Trans. Neural Networks, 2007

Forecasting the CATS benchmark with the Double Vector Quantization method.

Geoffroy Simon, John Aldo Lee, Marie Cottrell, Michel Verleysen

Neurocomputing, 2007

2006

Unfolding preprocessing for meaningful time series clustering.

Geoffroy Simon, John Aldo Lee, Michel Verleysen

Neural Networks, 2006

Non-orthogonal Support Width ICA.

John Aldo Lee, Frédéric Vrins, Michel Verleysen

Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006

2005

Nonlinear dimensionality reduction of data manifolds with essential loops.

John Aldo Lee, Michel Verleysen

Neurocomputing, 2005

Filtering-Free Blind Separation of Correlated Images.

Frédéric Vrins, John Aldo Lee, Michel Verleysen

Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Can we always trust entropy minima in the ICA context?

Frédéric Vrins, John Aldo Lee, Michel Verleysen

Proceedings of the 13th European Signal Processing Conference, 2005

A simple ICA algorithm for non-differentiable contrasts.

John Aldo Lee, Frédéric Vrins, Michel Verleysen

Proceedings of the 13th European Signal Processing Conference, 2005

2004

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis.

John Aldo Lee, Amaury Lendasse, Michel Verleysen

Neurocomputing, 2004

Non-linear ICA by Using Isometric Dimensionality Reduction.

John Aldo Lee, Christian Jutten, Michel Verleysen

Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

How to project 'circular' manifolds using geodesic distances?

John Aldo Lee, Michel Verleysen

Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

2003

Analysis of high-dimensional numerical data: from principal component analysis to non-linear dimensionality reduction and blind source separation.

John Aldo Lee

PhD thesis, 2003

Improving independent component analysis performances by variable selection.

Frédéric Vrins, John Aldo Lee, Michel Verleysen, Vincent Vigneron, Christian Jutten

Proceedings of the NNSP 2003, 2003

Locally Linear Embedding versus Isotop.

John Aldo Lee, Cédric Archambeau, Michel Verleysen

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures.

Cédric Archambeau, John Aldo Lee, Michel Verleysen

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002

Self-organizing maps with recursive neighborhood adaptation.

John Aldo Lee, Michel Verleysen

Neural Networks, 2002

Forecasting electricity consumption using nonlinear projection and self-organizing maps.

Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen

Neurocomputing, 2002

Nonlinear Projection with the Isotop Method.

John Aldo Lee, Michel Verleysen

Proceedings of the Artificial Neural Networks, 2002

Curvilinear Distance Analysis versus Isomap.

John Aldo Lee, Amaury Lendasse, Michel Verleysen

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Width optimization of the Gaussian kernels in Radial Basis Function Networks.

Nabil Benoudjit, Cédric Archambeau, Amaury Lendasse, John Aldo Lee, Michel Verleysen

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

2001

Recursive learning rules for SOMs.

John A. Lee, Nicolas Donckers, Michel Verleysen

Proceedings of the Advances in Self-Organising Maps, 2001

Input data reduction for the prediction of financial time series.

Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen

Proceedings of the 9th European Symposium on Artificial Neural Networks, 2001

2000

Time series forecasting using CCA and Kohonen maps - application to electricity consumption.

Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000

A robust non-linear projection method.

John Aldo Lee, Amaury Lendasse, Nicolas Donckers, Michel Verleysen

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000