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ORCIDJohn A. Lee 0001
John Aldo Lee
Person information
- affiliation: Université catholique de Louvain, Belgium
Other persons with the same name
- John A. Lee — disambiguation page
Other persons with a similar name
- Audrey St. John
![[0000-0002-4830-5781]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-4830-5781")
(aka: Audrey Lee-St. John, Audrey Lee) — Mount Holyoke College, South Hadley, MA, USA - John Lee — disambiguation page
- John A. N. Lee (aka: J. A. N. Lee) — Virginia Tech, Blacksburg, Virginia, USA
- John Boaz Lee
- John D. Lee
- John W. T. Lee (aka: John Wan Tung Lee)
- John Lee 0001 (aka: John S. Y. Lee, John Sie Yuen Lee) — City University of Hong Kong, Department of Linguistics and Translation, Hong Kong (and 1 more)
- John J. Lee 0001 (aka: Jaehwan John Lee, John Jaehwan Lee, Jaehwan Lee 0002) — Indiana University-Purdue University Indianapolis, Department of Electrical and Computer Engineering, IN, USA (and 1 more)
- John Lee 0004 (aka: John R. Lee 0001) — University of Edinburgh, UK
- John Malone-Lee (aka: John Charles Malone-Lee)
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2020 – today
- 2024
[j37]Viktor Wase, Sophie Wuyckens, John A. Lee, Michael Saint-Guillain:
The proton arc therapy treatment planning problem is NP-Hard. Comput. Biol. Medicine 171: 108139 (2024)- [j36]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
- [j35]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) - [c66]Ana Maria Barragán-Montero, Robin Tilman, Margerie Huet-Dastarac, John A. Lee:
Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer. ESANN 2023 - [c65]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 - [c64]Pierre Lambert, John A. Lee, Edouard Couplet, Cyril de Bodt:
Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration. ESANN 2023 - [i10]Margerie Huet-Dastarac, Dan Nguyen, Steve B. Jiang, John A. Lee, Ana M. Barragan-Montero:
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. CoRR abs/2310.19686 (2023) - 2022
- [j34]Daniel López Sánchez, Cyril de Bodt, John A. Lee, Angélica González Arrieta, Juan M. Corchado:
Tuning Database-Friendly Random Projection Matrices for Improved Distance Preservation on Specific Data. Appl. Intell. 52(5): 4927-4939 (2022) - [j33]Sophie Wuyckens, Michael Saint-Guillain, Guillaume Janssens, Lewei Zhao, Xiaoqiang Li, Xuanfeng Ding, Edmond Sterpin, John A. Lee, Kevin Souris:
Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers. Comput. Biol. Medicine 148: 105609 (2022) - [j32]Thomas Beznik, Paul Smyth, Gaël de Lannoy, John A. Lee:
Deep learning to detect bacterial colonies for the production of vaccines. Neurocomputing 470: 427-431 (2022) - [j31]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) - [j30]Stéphanie Guérit, Siddharth Sivankutty, John A. Lee, Hervé Rigneault, Laurent Jacques:
Compressive Imaging Through Optical Fiber with Partial Speckle Scanning. SIAM J. Imaging Sci. 15(2): 387-423 (2022) - [j29]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) - [i9]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
- [j28]Eliott Brion, Jean Léger, Ana M. Barragan-Montero, Nicolas Meert, John A. Lee, Benoît Macq:
Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT. Comput. Biol. Medicine 131: 104269 (2021) - [c63]Pierre Lambert, Cyril de Bodt, Michel Verleysen, John A. Lee:
Stochastic quartet approach for fast multidimensional scaling. ESANN 2021 - [c62]Pierre Lambert, John A. Lee, Michel Verleysen, Cyril de Bodt:
Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding. ESANN 2021 - [c61]John A. Lee, Alyssa Vanginderdeuren, Margerie Huet-Dastarac, Ana Maria Barragán-Montero:
Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models. ESANN 2021 - [i8]Stéphanie Guérit, Siddharth Sivankutty, John Aldo Lee, Hervé Rigneault, Laurent Jacques:
Compressive lensless endoscopy with partial speckle scanning. CoRR abs/2104.10959 (2021) - 2020
- [c60]Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu:
Perplexity-free Parametric t-SNE. ESANN 2020: 387-392 - [c59]Paul Smyth, John A. Lee, Gaël de Lannoy, Thomas Beznik:
Deep Learning to Detect Bacterial Colonies for the Production of Vaccines. ESANN 2020: 541-546 - [i7]Thomas Beznik, Paul Smyth, Gaël de Lannoy, John A. Lee:
Deep Learning to Detect Bacterial Colonies for the Production of Vaccines. CoRR abs/2009.00926 (2020) - [i6]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
- [j27]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) - [c58]Cyril de Bodt, Dounia Mulders, Daniel López Sánchez, Michel Verleysen, John A. Lee:
Class-aware t-SNE: cat-SNE. ESANN 2019 - [c57]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 - [c56]Eliott Brion, Jean Léger, Umair Javaid, John A. Lee, Christophe De Vleeschouwer, Benoît Macq:
Using planning CTs to enhance CNN-based bladder segmentation on cone beam CT. Medical Imaging: Image-Guided Procedures 2019: 109511M - [c55]Umair Javaid, Damien Dasnoy, John A. Lee:
Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation. Medical Imaging: Image Processing 2019: 109492P - 2018
- [j26]Yasir Hamid, Ludovic Journaux, John A. Lee, M. Sugumaran:
A novel method for network intrusion detection based on nonlinear SNE and SVM. Int. J. Artif. Intell. Soft Comput. 6(4): 265-286 (2018) - [c54]Umair Javaid, Damien Dasnoy, John A. Lee:
Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet. ACIVS 2018: 188-199 - [c53]Jean Léger, Eliott Brion, Umair Javaid, John A. Lee, Christophe De Vleeschouwer, Benoît Macq:
Contour Propagation in CT Scans with Convolutional Neural Networks. ACIVS 2018: 380-391 - [c52]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee:
Perplexity-free t-SNE and twice Student tt-SNE. ESANN 2018 - [c51]Cyril de Bodt, Dounia Mulders, Michel Verleysen, John A. Lee:
Extensive assessment of Barnes-Hut t-SNE. ESANN 2018 - [c50]Benoît Frénay, Bruno Dumas, John A. Lee:
Information visualisation and machine learning: latest trends towards convergence. ESANN 2018 - [c49]Umair Javaid, John A. Lee:
Capturing variabilities from Computed Tomography images with Generative Adversarial Networks (GANs). ESANN 2018 - [i5]Umair Javaid, John A. Lee:
Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks. CoRR abs/1805.11504 (2018) - [i4]Stéphanie Guérit, Siddharth Sivankutty, Camille Scotté, John Aldo Lee, Hervé Rigneault, Laurent Jacques:
Compressive Sampling Approach for Image Acquisition with Lensless Endoscope. CoRR abs/1810.12286 (2018) - 2017
- [j25]Romain Hérault, Dominic Orth, Ludovic Seifert, Jérémie Boulanger, John Aldo Lee:
Comparing dynamics of fluency and inter-limb coordination in climbing activities using multi-scale Jensen-Shannon embedding and clustering. Data Min. Knowl. Discov. 31(6): 1758-1792 (2017) - [j24]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) - [j23]Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, Daniel A. Keim:
What you see is what you can change: Human-centered machine learning by interactive visualization. Neurocomputing 268: 164-175 (2017) - [j22]Dominik Sacha, Leishi Zhang, Michael Sedlmair, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, Daniel A. Keim:
Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis. IEEE Trans. Vis. Comput. Graph. 23(1): 241-250 (2017) - [c48]Yasir Hamid, Ludovic Journaux, John Aldo Lee, Lucile Sautot, Nabi Bushra, M. Sugumaran:
Large-scale nonlinear dimensionality reduction for network intrusion detection. ESANN 2017 - 2016
- [c47]Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Daniel Weiskopf, Stephen C. North, Daniel A. Keim:
Human-centered machine learning through interactive visualization: review and open challenges. ESANN 2016 - [c46]Stéphanie Guérit, Laurent Jacques, John A. Lee:
Image deconvolution by local order preservation of pixels values. EUSIPCO 2016: 542-546 - [c45]Sergio García-Vega, Germán Castellanos-Domínguez, Michel Verleysen, John Aldo Lee:
Multi-step-ahead forecasting using kernel adaptive filtering. IJCNN 2016: 2132-2139 - [i3]Stéphanie Guérit, Adriana Gonzalez, Anne Bol, John A. Lee, Laurent Jacques:
Blind Deconvolution of PET Images using Anatomical Priors. CoRR abs/1608.01896 (2016) - [i2]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:
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR abs/1609.04167 (2016) - 2015
- [j21]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental classification of objects in scenes: Application to the delineation of images. Neurocomputing 152: 45-57 (2015) - [j20]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) - [c44]Kerstin Bunte, John Aldo Lee:
Unsupervised dimensionality reduction: the challenge of big data visualization. ESANN 2015 - [c43]Diego Hernán Peluffo-Ordóñez, Juan Carlos Alvarado-Pérez, John Aldo Lee, Michel Verleysen:
Geometrical homotopy for data visualization. ESANN 2015 - [c42]Stéphanie Guérit, Laurent Jacques, Benoît Macq, John A. Lee:
Post-reconstruction deconvolution of PET images by total generalized variation regularization. EUSIPCO 2015: 629-633 - [c41]Romain Hérault, Jérémie Boulanger, Ludovic Seifert, John Aldo Lee:
Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding. MLSA@PKDD/ECML 2015: 18-27 - [i1]Stéphanie Guérit, Laurent Jacques, Benoît Macq, John A. Lee:
Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization. CoRR abs/1506.04935 (2015) - 2014
- [j19]Mark J. Embrechts, Fabrice Rossi, Frank-Michael Schleif, John Aldo Lee:
Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013). Neurocomputing 141: 1-2 (2014) - [c40]John Aldo Lee, Michel Verleysen:
Two key properties of dimensionality reduction methods. CIDM 2014: 163-170 - [c39]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen:
Generalized kernel framework for unsupervised spectral methods of dimensionality reduction. CIDM 2014: 171-177 - [c38]John Aldo Lee, Diego Hernán Peluffo-Ordóñez, Michel Verleysen:
Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction. ESANN 2014 - [c37]Diego Hernán Peluffo-Ordóñez, John Aldo Lee, Michel Verleysen:
Recent methods for dimensionality reduction: A brief comparative analysis. ESANN 2014 - [c36]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 - [c35]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
- [j18]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) - [c34]Francisco J. García-Fernández, Michel Verleysen, John Aldo Lee, Ignacio Díaz Blanco:
Sensitivity to parameter and data variations in dimensionality reduction techniques. ESANN 2013 - [c33]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Segmentation with Incremental Classifiers. ICIAP (2) 2013: 81-90 - [c32]Michel Verleysen, John Aldo Lee:
Nonlinear Dimensionality Reduction for Visualization. ICONIP (1) 2013: 617-622 - [c31]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 - [c30]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 - 2012
- [j17]John Aldo Lee, Petra Schneider, John A. Quinn:
Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011). Neurocomputing 90: 1-2 (2012) - [j16]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:
Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy. IEEE Trans. Medical Imaging 31(11): 2006-2024 (2012) - [c29]Guillaume Bernard, Michel Verleysen, John Aldo Lee:
Incremental feature building and classification for image segmentation. ESANN 2012 - [c28]John Aldo Lee:
Type 1 and 2 symmetric divergences for stochastic neighbor embedding. ESANN 2012 - 2011
- [j15]John Aldo Lee, Frank-Michael Schleif, Thomas Martinetz:
Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing 74(9): 1299-1300 (2011) - [j14]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) - [c27]John Aldo Lee, Michel Verleysen:
Shift-invariant similarities circumvent distance concentration in stochastic neighbor embedding and variants. ICCS 2011: 538-547 - 2010
- [j13]Cecilio Angulo, John Aldo Lee, Frank-Michael Schleif:
Advances in computational intelligence and learning (ESANN 2009). Neurocomputing 73(7-9): 1049-1050 (2010) - [j12]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) - [j11]John Aldo Lee, Michel Verleysen:
Scale-independent quality criteria for dimensionality reduction. Pattern Recognit. Lett. 31(14): 2248-2257 (2010) - [c26]John A. Lee, Michel Verleysen:
On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding. COMPSTAT 2010: 337-346 - [c25]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 - [c24]Axel Wismüller, Michel Verleysen, Michaël Aupetit, John Aldo Lee:
Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning. ESANN 2010 - [c23]John Aldo Lee, Michel Verleysen:
Unsupervised dimensionality reduction: Overview and recent advances. IJCNN 2010: 1-8 - [c22]Victor Onclinx, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Dimensionality reduction by rank preservation. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j10]John Aldo Lee, Michel Verleysen:
Quality assessment of dimensionality reduction: Rank-based criteria. Neurocomputing 72(7-9): 1431-1443 (2009) - [c21]Arnaud de Decker, John Aldo Lee, Michel Verleysen:
Patch-based bilateral filter and local m-smoother for image denoising. ESANN 2009 - [c20]John Aldo Lee, Arnaud de Decker, Michel Verleysen:
Adaptive anisotropic denoising: a bootstrapped procedure. ESANN 2009 - [c19]John Aldo Lee, Michel Verleysen:
Simbed: Similarity-Based Embedding. ICANN (2) 2009: 95-104 - 2008
- [j9]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) - [j8]John Aldo Lee, Xavier Geets, Vincent Grégoire, Anne Bol:
Edge-Preserving Filtering of Images with Low Photon Counts. IEEE Trans. Pattern Anal. Mach. Intell. 30(6): 1014-1027 (2008) - [c18]John Aldo Lee, Michel Verleysen:
Rank-based quality assessment of nonlinear dimensionality reduction. ESANN 2008: 49-54 - [c17]John Aldo Lee, Michel Verleysen:
Quality assessment of nonlinear dimensionality reduction based on K-ary neighborhoods. FSDM 2008: 21-35 - 2007
- [j7]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) - [j6]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) - 2006
- [j5]Geoffroy Simon, John Aldo Lee, Michel Verleysen:
Unfolding preprocessing for meaningful time series clustering. Neural Networks 19(6-7): 877-888 (2006) - [c16]John Aldo Lee, Frédéric Vrins, Michel Verleysen:
Non-orthogonal Support Width ICA. ESANN 2006: 351-358 - 2005
- [j4]John Aldo Lee, Michel Verleysen:
Nonlinear dimensionality reduction of data manifolds with essential loops. Neurocomputing 67: 29-53 (2005) - [c15]John Aldo Lee, Frédéric Vrins, Michel Verleysen:
A simple ICA algorithm for non-differentiable contrasts. EUSIPCO 2005: 1-4 - [c14]Frédéric Vrins, John Aldo Lee, Michel Verleysen:
Can we always trust entropy minima in the ICA context? EUSIPCO 2005: 1-4 - [c13]Frédéric Vrins, John Aldo Lee, Michel Verleysen:
Filtering-Free Blind Separation of Correlated Images. IWANN 2005: 1091-1099 - 2004
- [j3]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis. Neurocomputing 57: 49-76 (2004) - [c12]John Aldo Lee, Michel Verleysen:
How to project 'circular' manifolds using geodesic distances? ESANN 2004: 223-230 - [c11]John Aldo Lee, Christian Jutten, Michel Verleysen:
Non-linear ICA by Using Isometric Dimensionality Reduction. ICA 2004: 710-717 - 2003
- [b1]John Aldo Lee:
Analysis of high-dimensional numerical data: from principal component analysis to non-linear dimensionality reduction and blind source separation. Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2003 - [c10]Cédric Archambeau, John Aldo Lee, Michel Verleysen:
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures. ESANN 2003: 99-106 - [c9]John Aldo Lee, Cédric Archambeau, Michel Verleysen:
Locally Linear Embedding versus Isotop. ESANN 2003: 527-534 - [c8]Frédéric Vrins, John Aldo Lee, Michel Verleysen, Vincent Vigneron, Christian Jutten:
Improving independent component analysis performances by variable selection. NNSP 2003: 359-368 - 2002
- [j2]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) - [j1]John Aldo Lee, Michel Verleysen:
Self-organizing maps with recursive neighborhood adaptation. Neural Networks 15(8-9): 993-1003 (2002) - [c7]John Aldo Lee, Amaury Lendasse, Michel Verleysen:
Curvilinear Distance Analysis versus Isomap. ESANN 2002: 185-192 - [c6]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 - [c5]John Aldo Lee, Michel Verleysen:
Nonlinear Projection with the Isotop Method. ICANN 2002: 933-938 - 2001
- [c4]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 - [c3]John A. Lee, Nicolas Donckers, Michel Verleysen:
Recursive learning rules for SOMs. WSOM 2001: 67-72 - 2000
- [c2]John Aldo Lee, Amaury Lendasse, Nicolas Donckers, Michel Verleysen:
A robust non-linear projection method. ESANN 2000: 13-20 - [c1]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
Coauthor Index
[j36] [j35] [c65] [j31] [j29] [i9] [c63] [c62] [c60] [i6] [j27] [c58] [c57] [c52] [c51] [j24] [c45] [j21] [j20] [c43] [c40] [c39] [c38] [c37] [c36] [c35] [j18] [c34] [c33] [c32] [c31] [c30] [c29] [j14] [c27] [j12] [j11] [c26] [c25] [c24] [c23] [c22] [j10] [c21] [c20] [c19] [j9] [c18] [c17] [j7] [j6] [j5] [c16] [j4] [c15] [c14] [c13] [j3] [c12] [c11] [c10] [c9] [c8] [j2] [j1] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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last updated on 2024-11-06 21:31 CET by the dblp team
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