John Aldo Lee

发表

Non-orthogonal Support Width ICA

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2006, ESANN.

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

Michel Verleysen, John Aldo Lee, Arnaud de Decker, 2009, ESANN.

Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding

Romain Hérault, John Aldo Lee, Ludovic Seifert, 2015, MLSA@PKDD/ECML.

EP-1821 Fast Robust Optimization using a Patient-Specific Scenario Selection Methodology

John Aldo Lee, G. Buti, K. Souris, 2019 .

Type 1 and 2 symmetric divergences for stochastic neighbor embedding

John Aldo Lee, 2012, ESANN.

Unsupervised dimensionality reduction: from principal component analysis to modern nonlinear techniques

John Aldo Lee, Michel Verleysen, 2010 .

Advances in computational intelligence and learning

Frank-Michael Schleif, Cecilio Angulo, John Aldo Lee, 2010 .

High-Dimensional Data

Michel Verleysen, John Aldo Lee, M. Verleysen, 2007 .

Michel Verleysen, Diego Hernán Peluffo-Ordóñez, John Aldo Lee, 2015, Neurocomputing.

Edge-Preserving Filtering of Images with Low Photon Counts

John Aldo Lee, Anne Bol, Xavier Geets, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Locally Linear Embedding versus Isotop

Michel Verleysen, John Aldo Lee, Cédric Archambeau, 2003, ESANN.

Unsupervised dimensionality reduction: Overview and recent advances

Michel Verleysen, John Aldo Lee, M. Verleysen, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

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

Xiaodong Wu, Habib Zaidi, Valery Naranjo, 2013, IEEE Transactions on Medical Imaging.

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

Romain Hérault, John Aldo Lee, Ludovic Seifert, 2017, Data Mining and Knowledge Discovery.

Self-organizing maps with recursive neighborhood adaptation

Michel Verleysen, John Aldo Lee, M. Verleysen, 2002, Neural Networks.

Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning

Michel Verleysen, Axel Wismüller, John Aldo Lee, 2010, ESANN.

A robust nonlinear projection method

Amaury Lendasse, John Aldo Lee, Michel Verleysen, 2000 .

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

Michel Verleysen, John Aldo Lee, M. Verleysen, 2010, COMPSTAT.

Improving projection-based data analysis by feature space transformations

Michel Verleysen, Daniel A. Keim, Tobias Schreck, 2013, Electronic Imaging.

A robust non-linear projection method

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2000, ESANN.

OC-0070: Automatic dose painting workflow: from tumor segmentation to optimization

John Aldo Lee, Edmond Sterpin, A Barragan Montero, 2015 .

Simulation and reconstruction of PET images: application to attenuation correction using CT images

John Aldo Lee, Anne Bol, Kevin Souris, 2013 .

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

Michel Verleysen, John Aldo Lee, Guillaume Bernard, 2015, Neurocomputing.

Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2004, Neurocomputing.

Curvilinear Distance Analysis versus Isomap

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2002, ESANN.

Assessing the robustness of proton therapy plans using fast Monte Carlo tools

John Aldo Lee, Kevin Souris, Edmond Sterpin, 2015 .

How to project 'circular' manifolds using geodesic distances?

Michel Verleysen, John Aldo Lee, 2004, ESANN.

Design and Deployment of a Proton Therapy Cone-Beam CT

John Aldo Lee, Rudi Labarbe, Sébastien Brousmiche, 2012 .

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

Michel Verleysen, John Aldo Lee, M. Verleysen, 2008, FSDM.

Multiscale stochastic neighbor embedding: Towards parameter-free dimensionality reduction

Michel Verleysen, Diego Hernán Peluffo-Ordóñez, John Aldo Lee, 2014, ESANN.

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

Michel Verleysen, John Aldo Lee, Arnaud de Decker, 2011, ESANN.

Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis

Daniel A. Keim, Daniel Weiskopf, Jaakko Peltonen, 2017, IEEE Transactions on Visualization and Computer Graphics.

PO-0783: design of cone-beam CT for proton therapy gantry

Benoît Macq, John Aldo Lee, Rudi Labarbe, 2014 .

Can we always trust entropy minima in the ICA context?

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2005, 2005 13th European Signal Processing Conference.

Non-linear ICA by Using Isometric Dimensionality Reduction

Michel Verleysen, Christian Jutten, John Aldo Lee, 2004, ICA.

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

John Aldo Lee, Yasir Hamid, M. Sugumaran, 2017 .

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

Thomas Martinetz, Frank-Michael Schleif, John Aldo Lee, 2011, Neurocomputing.

Short Review of Dimensionality Reduction Methods Based on Stochastic Neighbour Embedding

Michel Verleysen, Diego Hernán Peluffo-Ordóñez, John Aldo Lee, 2014, WSOM.

Forecasting electricity consumption using nonlinear projection and self-organizing maps

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2002, Neurocomputing.

Nonlinear Projection with the Isotop Method

Michel Verleysen, John Aldo Lee, M. Verleysen, 2002, ICANN.

Input data reduction for the prediction of financial time series

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2001, ESANN.

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

Michel Verleysen, Pierre Dupont, John Aldo Lee, 2013, Neurocomputing.

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

John Aldo Lee, Kevin Souris, Edmond Sterpin, 2015 .

Methodological Study of Geometric Deformation for CBCT in Proton Therapy Gantry

John Aldo Lee, Benoît Macq, Rudi Labarbe, 2011 .

A Minimum-Range Approach to Blind Extraction of Bounded Sources

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2007, IEEE Transactions on Neural Networks.

Unfolding preprocessing for meaningful time series clustering

Michel Verleysen, John Aldo Lee, Geoffroy Simon, 2006, Neural Networks.

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

Daniel A. Keim, Daniel Weiskopf, John Aldo Lee, 2016, ESANN.

Universal Dependencies 2.1

Yuji Matsumoto, Isabelle Tellier, Nizar Habash, 2017 .

Large-scale nonlinear dimensionality reduction for network intrusion detection

John Aldo Lee, Lucile Sautot, M. Sugumaran, 2017, ESANN.

Compressive Sampling Approach for Image Acquisition with Lensless Endoscope pdf

Laurent Jacques, Siddharth Sivankutty, John Aldo Lee, 2018, ArXiv.

Fast Monte Carlo simulation of proton therapy treatment using an Intel Xeon Phi coprocessor

John Aldo Lee, Kevin Souris, Edmond Sterpin, 2014 .

Incremental feature computation and classification for image segmentation

John Aldo Lee, Michel Verleysen, Guillaume Bernard, 2012 .

Nonlinear dimensionality reduction of data manifolds with essential loops

Michel Verleysen, John Aldo Lee, 2005, Neurocomputing.

Nonlinear Dimensionality Reduction

Michel Verleysen, John Aldo Lee, P. Fua, 2021, Computer Vision.

Scale-independent quality criteria for dimensionality reduction

Michel Verleysen, John Aldo Lee, M. Verleysen, 2010, Pattern Recognit. Lett..

Segmentation with Incremental Classifiers

Michel Verleysen, John Aldo Lee, Guillaume Bernard, 2013, ICIAP.

How to assess the quality of nonlinear dimensionality reduction techniques

John Aldo Lee, Michel Verleysen, 2009 .

Width optimization of the Gaussian kernels in Radial Basis Function Networks

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2002, ESANN.

Simbed: Similarity-Based Embedding

Michel Verleysen, John Aldo Lee, M. Verleysen, 2009, ICANN.

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

John Aldo Lee, 2003 .

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

Frank-Michael Schleif, Fabrice Rossi, John Aldo Lee, 2014, Neurocomputing.

Sensitivity to parameter and data variations in dimensionality reduction techniques

Michel Verleysen, John Aldo Lee, Ignacio Díaz Blanco, 2013, ESANN.

Tensor factorization to extract patterns in multimodal EEG data

John Aldo Lee, Michel Verleysen, Dounia Mulders, 2019, ESANN.

A novel supervised watershed method for segmentation of tumors with heterogeneous tracer uptake in PET

John Aldo Lee, Ronald Boellaard, X. Geets, 2014 .

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

John A. Quinn, Petra Schneider, John Aldo Lee, 2012, Neurocomputing.

Contour Propagation in CT Scans with Convolutional Neural Networks

Christophe De Vleeschouwer, Benoît Macq, John Aldo Lee, 2018, ACIVS.

On the need of unfolding preprocessing for time series clustering

Michel Verleysen, John Aldo Lee, Geoffroy Simon, 2005 .

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

Michel Verleysen, Amaury Lendasse, John Aldo Lee, 2000, ESANN.

Quality assessment of dimensionality reduction: Rank-based criteria

Michel Verleysen, John Aldo Lee, M. Verleysen, 2009, Neurocomputing.

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

Daniel A. Keim, Daniel Weiskopf, Jaakko Peltonen, 2017, Neurocomputing.

The intrusion-extrusion compromise for the projection and visualization of high-dimensional data

John Aldo Lee, Michel Verleysen, 2009 .

Human-centered machine learning through interactive visualization

Daniel A. Keim, Daniel Weiskopf, John Aldo Lee, 2016 .

Adaptive anisotropic denoising: a bootstrapped procedure

Michel Verleysen, John Aldo Lee, Arnaud de Decker, 2009, ESANN.

On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures

Michel Verleysen, John Aldo Lee, Cédric Archambeau, 2003, ESANN.

Dimensionality reduction by rank preservation

Michel Verleysen, John Aldo Lee, Vincent Wertz, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Nonlinear Dimensionality Reduction for Visualization

Michel Verleysen, John Aldo Lee, M. Verleysen, 2013, ICONIP.

Geometrical homotopy for data visualization

Michel Verleysen, Juan C. Alvarado-Pérez, Diego Hernán Peluffo-Ordóñez, 2015, ESANN.

Approximation by radial basis function networks

Michel Verleysen, John Aldo Lee, Vincent Wertz, 2003 .

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

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2008, Neurocomputing.

Incremental feature building and classification for image segmentation

Michel Verleysen, John Aldo Lee, Guillaume Bernard, 2012, ESANN.

Advances in computational intelligence and learning (ESANN 2009)

Frank-Michael Schleif, Cecilio Angulo, John Aldo Lee, 2010, Neurocomputing.

Unsupervised dimensionality reduction: the challenge of big data visualization

John Aldo Lee, Kerstin Bunte, K. Bunte, 2015, ESANN.

Recent methods for dimensionality reduction: A brief comparative analysis

Michel Verleysen, Diego Hernán Peluffo-Ordóñez, John Aldo Lee, 2014, ESANN.

Development of a software platform for evaluating automatic PET segmentation methods

Habib Zaidi, John Aldo Lee, E. De Bernardi, 2014 .

Valuation of climbing activities using Multi-Scale Jensen-Shannon Neighbour Embedding

Romain Hérault, John Aldo Lee, Ludovic Seifert, 2017 .

Filtering-Free Blind Separation of Correlated Images

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2005, IWANN.

Improving independent component analysis performances by variable selection

Michel Verleysen, Frédéric Vrins, Christian Jutten, 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

Time Series Forecasting using CCA and Kohonen Maps - Applications to Electricity Consumption

Amaury Lendasse, Vincent Wertz, John Aldo Lee, 2000 .

Generalized kernel framework for unsupervised spectral methods of dimensionality reduction

Michel Verleysen, Diego Hernán Peluffo-Ordóñez, John Aldo Lee, 2014, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

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

John Aldo Lee, Umair Javaid, Damien Dasnoy, 2018, ACIVS.

Cross-Domain Data Augmentation for Deep-Learning-Based Male Pelvic Organ Segmentation in Cone Beam CT

Christophe De Vleeschouwer, John Aldo Lee, Eliott Brion, 2020, Applied Sciences.

Multi-step-ahead forecasting using kernel adaptive filtering

Michel Verleysen, Germán Castellanos-Domínguez, John Aldo Lee, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Dimension reduction of technical indicators for the prediction of financial time series - Application to the BEL20 Market Index

Michel Verleysen, John Aldo Lee, Vincent Wertz, 2001 .

Rank-based quality assessment of nonlinear dimensionality reduction

Michel Verleysen, John Aldo Lee, M. Verleysen, 2008, ESANN.

A principled approach to image denoising with similarity kernels involving patches

Michel Verleysen, John Aldo Lee, Arnaud de Decker, 2010, Neurocomputing.

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

Michel Verleysen, Andrés Marino Álvarez-Meza, Germán Castellanos-Domínguez, 2017, Neurocomputing.

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

Michel Verleysen, John Aldo Lee, M. Verleysen, 2011, ICCS.

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

Michel Verleysen, Germán Castellanos-Domínguez, Diego Hernán Peluffo-Ordóñez, 2014, ICPRAM.

Performance Assessment of Patch-based Bilateral Denoising

John Aldo Lee, Michel Verleysen, Arnaud De Decker, 2018 .

Forecasting the CATS benchmark with the Double Vector Quantization method

Michel Verleysen, John Aldo Lee, Marie Cottrell, 2007, Neurocomputing.

A simple ICA algorithm for non-differentiable contrasts

Michel Verleysen, Frédéric Vrins, John Aldo Lee, 2005, 2005 13th European Signal Processing Conference.

Recursive learning rules for SOMs

John Aldo Lee, Michel Verleysen, Nicolas Donckers, 2001, WSOM.